Yuichi Mori

• Maeda, Yasuharu; Kudo, Shin Ei; Ogata, Noriyuki; Takenaka, Kento; Takabayashi, Kaoru & Kuroki, Takanori [Vis alle 18 forfattere av denne artikkelen] (2026). AI-based quantification of inflammatory extent for relapse prediction in ulcerative colitis: a prospective cohort study. Journal of Crohn's and Colitis. ISSN 1873-9946. 20(7), s. 1–10. doi: 10.1093/ecco-jcc/jjag115. Fulltekst i vitenarkiv
• Ahmad, Omer F.; Mori, Yuichi; Bretthauer, Michael; Dourado, Daniel A.; Hassan, Cesare & Bisschops, Raf [Vis alle 20 forfattere av denne artikkelen] (2025). The Legal and Ethical Framework for Artificial Intelligence in Gastrointestinal Endoscopy: A World Endoscopy Organization International Consensus Statement. Annals of Internal Medicine. ISSN 0003-4819. 179(2), s. 270–275. doi: 10.7326/annals-25-03415. Fulltekst i vitenarkiv
• Massimi, Davide; Carlini, Luca; Mori, Yuichi; Stefano, Luca Di; Antonelli, Giulio & Rizkala, Tommy [Vis alle 22 forfattere av denne artikkelen] (2025). Large language model for interpreting the Paris classification of colorectal polyps. Endoscopy International Open. 13(CP). doi: 10.1055/a-2703-0209. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Reporting of colorectal polyp morphology using the Paris classification is often inaccurate. Multimodal large language models (M-LLMs) may support morphological assessment. This study aimed to evaluate the accuracy of an M-LLM (GPT-4o) in classifying colorectal polyp morphology compared with expert and non-expert endoscopists. We used the SUN dataset of colonoscopy videos from 100 unique colorectal polyps, each labeled with the validated Paris classification. An M-LLM (GPT-4o) classified five representative frames per lesion. Three expert and three non-expert endoscopists, blinded to one another, performed the same task. The primary outcome was accuracy in differentiating non-polypoid (IIa/IIc) from polypoid (Is/Ip/Isp) lesions. The secondary outcome was accuracy in differentiating sessile (Is) from pedunculated (Ip/Isp) lesions. Given the exploratory design, no multiplicity correction was applied; point estimates are presented with 95% confidence intervals (CIs), and P values are interpreted descriptively. M-LLM accuracy for differentiating non-polypoid from polypoid lesions was 73% (95% CI 63%-81%), comparable to experts (75%, 65%-83%; P = 0.84) and non-experts (77%, 68%-85%; P = 0.52), with similar sensitivity and specificity. Accuracy for differentiating sessile from pedunculated lesions was 55% (95% CI 42%-67%), lower than experts (76%; P = 0.02) and non-experts (77%; P = 0.01), primarily due to poor specificity (12% vs. experts 82% and non-experts 88%; P < 0.01 for both comparisons). M-LLMs performed comparably to endoscopists in distinguishing non-polypoid from polypoid lesions but failed to reliably identify pedunculated morphology.

• Muccichini, Enrico; Rondonotti, Emanuele; Spadaccini, Marco; Segatta, Francesco; Savino, Alberto & Paggi, Silvia [Vis alle 14 forfattere av denne artikkelen] (2025). Bowel preparation quality and computer-aided detection of adenomas during colonoscopy. Digestive and Liver Disease. ISSN 1590-8658. 57(11), s. 2179–2179. doi: 10.1016/j.dld.2025.08.072. Fulltekst i vitenarkiv
• Coelho-Prabhu, Nayantara; Bhat, Purnima; Kalapala, Rakesh; Mushtaq, Junaid; Tajiri, Hisao & Mori, Yuichi (2025). World Endoscopy Organization's Response to the World Health Organization's Global Initiative on Artificial Intelligence for Health. Digestive Endoscopy. ISSN 0915-5635. 37(11), s. 1143–1147. doi: 10.1111/den.70011. Fulltekst i vitenarkiv Vis sammendrag

  In response to the World Health Organization’s (WHO) Global Initiative on Artificial Intelligence(AI) for Health, the World Endoscopy Organization (WEO) highlights the unique challenges and opportunities AI presents for gastrointestinal endoscopy, particularly in resource-limited settings. While AI technologies have shown promise in improving diagnostic accuracy and efficiency in high resource environments, their implementation in low- and middle-income countries is hindered by infrastructural, economic, regulatory, and training barriers. This commentary explores how these challenges may exacerbate existing healthcare disparities, emphasizing the need for localized datasets, affordable AI models, simplified regulatory frameworks, and workforce capacity-building. The WEO supports WHO’s call for equitable AI deployment and advocates for region-specific solutions, including mobile and offline AI tools, public-private partnerships, locally developed algorithms aligned with prevalent disease patterns, and flexibly adapted regulatory framework. By leveraging WEO’s training networks and fostering collaboration among governments, clinicians, and industry, the integration of AI into endoscopy can become more accessible and relevant to underserved populations. The commentary underscores that AI should not be seen as a luxury but as a tool to bridge global disparities in care quality. Ensuring responsible and inclusive AI integration requires both global coordination and context-specific adaptations to truly benefit all healthcare systems.

• Rex, Douglas K.; Guardiola, John J.; Renteln, Daniel von; Mori, Yuichi; Sharma, Prateek & Hassan, Cesare (2025). Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot. Gut. ISSN 0017-5749. 74(6), s. 881–883. doi: 10.1136/gutjnl-2024-334456. Fulltekst i vitenarkiv
• Kuroki, Takanori; Maeda, Yasuharu; Kudo, Shin-Ei; Ogata, Noriyuki; Takabayashi, Kaoru & Takenaka, Kento [Vis alle 20 forfattere av denne artikkelen] (2025). Combination of white-light imaging–based and narrow-band imaging–based artificial intelligence models during colonoscopy in patients with ulcerative colitis. Journal of Crohn's and Colitis. ISSN 1873-9946. 19(1). doi: 10.1093/ecco-jcc/jjaf014. Fulltekst i vitenarkiv
• Mori, Yuichi & Misawa, Masashi (2025). Quality assessment in endoscopy “artificial intelligence in endoscopy”. Baillière's Best Practice & Research Clinical Gastroenterology. ISSN 1521-6918. 76. doi: 10.1016/j.bpg.2025.102006. Fulltekst i vitenarkiv
• Halvorsen, Natalie Grace Mosteiro; Barua, Ishita; Kudo, Shin-Ei; Gulati, Shraddha; Misawa, Masashi & Mori, Kensaku [Vis alle 19 forfattere av denne artikkelen] (2025). Leaving colorectal polyps in situ with endocytoscopy assisted by computer-aided diagnosis: a cost-effectiveness study. Endoscopy. ISSN 0013-726X. 57, s. 611–619. doi: 10.1055/a-2532-9282. Fulltekst i vitenarkiv
• Ogata, Noriyuki; Maeda, Yasuharu; Misawa, Masashi; Takenaka, Kento; Takabayashi, Kaoru & Iacucci, Marietta [Vis alle 24 forfattere av denne artikkelen] (2025). Artificial Intelligence-assisted Video Colonoscopy for Disease Monitoring of Ulcerative Colitis: A Prospective Study. Journal of Crohn's and Colitis. ISSN 1873-9946. 19(1). doi: 10.1093/ecco-jcc/jjae080. Fulltekst i vitenarkiv
• Storås, Andrea; Dreyer, Maximilian; Pahde, Frederik; Lapuschkin, Sebastian; Samek, Wojciech & Halvorsen, Pål [Vis alle 12 forfattere av denne artikkelen] (2025). Exploring the clinical value of concept-based AI explanations in gastrointestinal disease detection. Scientific Reports. 15. doi: 10.1038/s41598-025-14408-y. Fulltekst i vitenarkiv Vis sammendrag

  Complex artificial intelligence models, like deep neural networks, have shown exceptional capabilities to detect early-stage polyps and tumors in the gastrointestinal tract. These technologies are already beginning to assist gastroenterologists in the endoscopy suite. To understand how these complex models work and their limitations, model explanations can be useful. Moreover, medical doctors specialized in gastroenterology can provide valuable feedback on the model explanations. This study explores three different explainable artificial intelligence methods for explaining a deep neural network detecting gastrointestinal abnormalities. The model explanations are presented to gastroenterologists. Furthermore, the clinical applicability of the explanation methods from the healthcare personnel’s perspective is discussed. Our findings indicate that the explanation methods are not meeting the requirements for clinical use, but that they can provide valuable information to researchers and model developers. Higher quality datasets and careful considerations regarding how the explanations are presented might lead to solutions that are more welcome in the clinic.

• Capogreco, Antonio; Maselli, Roberta; Enderle, Markus; Salkic, Nermin; Keller, Sandra & Gaetano, Francesco De [Vis alle 16 forfattere av denne artikkelen] (2025). Different behavior of electrosurgical currents between air and saline immersion therapeutic endoscopy. Scientific Reports. 15(1). doi: 10.1038/s41598-024-83503-3. Fulltekst i vitenarkiv
• Spadaccini, Marco; Hassan, Cesare; Mori, Yuichi; Massimi, Davide; Correale, Loredana & Facciorusso, Antonio [Vis alle 16 forfattere av denne artikkelen] (2025). Variability in computer-aided detection effect on adenoma detection rate in randomized controlled trials: A meta-regression analysis. Digestive and Liver Disease. ISSN 1590-8658. 57(6), s. 1141–1148. doi: 10.1016/j.dld.2025.01.192. Fulltekst i vitenarkiv
• Gadi, Sanjay R.V.; Mori, Yuichi; Misawa, Masashi; East, James E.; Hassan, Cesare & Repici, Alessandro [Vis alle 30 forfattere av denne artikkelen] (2025). Creating a standardized tool for the evaluation and comparison of artificial intelligence–based computer-aided detection programs in colonoscopy: a modified Delphi approach. Gastrointestinal Endoscopy. ISSN 0016-5107. 102(1), s. 109–116.e2. doi: 10.1016/j.gie.2024.11.042. Fulltekst i vitenarkiv
• Hassan, Cesare; Rizkala, Tommy; Mori, Yuichi; Spadaccini, Marco; Misawa, Masashi & Antonelli, Giulio [Vis alle 31 forfattere av denne artikkelen] (2024). Computer-Aided Diagnosis for the Resect and Discard Strategy for Colorectal Polyps: A Systematic Review and Meta-Analysis. The Lancet Gastroenterology and Hepatology. ISSN 2468-1253. 9(11), s. 1010–1019. doi: 10.1016/S2468-1253(24)00222-X. Fulltekst i vitenarkiv Vis sammendrag

  Background: The Resect and Discard strategy allows endoscopists to replace post-polypectomy pathology with real-time prediction of polyp histology during colonoscopy (optical diagnosis). The present systematic review and meta-analysis investigated how the implementation of computer-aided diagnosis (CADx) for polyp pathology affected the Resect and Discard strategy. Methods: We conducted a search of MEDLINE, EMBASE, and Scopus databases, covering studies published from inception to June 5, 2024. No language restrictions were applied. We included diagnostic accuracy studies that evaluated the real-time optical diagnosis performance of CADx systems, as compared to histology, for polyps ≤5mm in the entire colon. The aim was to estimate the potential benefits and harms associated with integrating CADx assistance into the endoscopist optical diagnosis, both before and after its implementation. The primary outcome were the proportion of polyps that would have avoided pathological assessment (main benefit) and the proportion of polyps incorrectly predicted (main harm) due to false-positive or -negative optical diagnosis. When the endoscopists were involved in the optical diagnosis, our analysis included only their predictions made with high confidence. We used a random effect model to calculate all outcomes. Findings: Our literature search identified a total of 377 studies, 11 of which met eligibility criteria. A total of 11 studies with 7,400 polyps were eligible for analysis. Three studies (1,817 patients; A total of 11 studies with 7,400 polyps were eligible for analysis. Three studies (1,817 patients; 4,086 polyps) provided data to directly compare the primary benefit/harm outcome measures between the CADx-unassisted and CADx-assisted strategies. There was no significant difference between the CADx-unassisted and CADx-assisted strategies for the proportion of polyps that would have avoided pathological assessment (3,588/4,086, 90% vs. 3,653/4,086 90%; risk ratio: 1.01; 95% CI: 0.99, 1.04; I^2 108 =53.49%; low certainty evidence; 3 studies; Egger test p=0.18). CADx-assisted strategy reduced the proportion of incorrectly predicted polyps as compared with CADx-unassisted strategy (582/3,588, 13% vs. 523/3,653, 12%; risk ratio: 0.88; 95% CI: 0.79, 0.98; I^2=0%; low certainty evidence; 3 studies; Egger test p=0.18) mainly due to a decrease in false positive diagnosis. Interpretation: CADx-assistance failed to improve the main outcomes of Resect-and-Discard strategy in clinical studies, questioning its value in clinical practice. Funding: European Commission (Horizon Europe 101057099). The Japan Society of Promotion of Science (No. 22H03357). Associazione Italiana per la Ricerca sul Cancro (AIRC): IG 2022 – ID. 27843 project – P.I. Hassan Cesare. Registration: PROSPERO CRD42024508440

• Hassan, Cesare; Misawa, Masashi; Rizkala, Tommy; Mori, Yuichi; Sultan, Shahnaz & Facciorusso, Antonio [Vis alle 26 forfattere av denne artikkelen] (2024). Computer-Aided Diagnosis for Leaving-In-Situ of Colorectal Polyps: A Systematic Review and Meta-analysis. Annals of Internal Medicine. ISSN 0003-4819. 177(7), s. 919–929. doi: 10.7326/M23-2865. Fulltekst i vitenarkiv Vis sammendrag

  Backround: Computer-aided diagnosis (CADx) allows prediction of polyp histology during colonoscopy, which may reduce unnecessary removal of nonneoplastic polyps. However, the benefits and potential harms of CADx are still unclear. Purpose: To quantify the benefit and harm of using CADx in colonoscopy for the optical diagnosis of small (≤5-mm) rectosigmoid polyps. Data Sources: Medline, Embase, and Scopus were searched for articles published before 22 December 2023. Study Selection: Histologically verified diagnostic accuracy studies that evaluated the real-time performance of physicians in predicting neoplastic change of small rectosigmoid polyps without or with CADx assistance during colonoscopy. Data Extraction: The clinical benefit and harm were estimated on the basis of accuracy values of the endoscopist before and after CADx assistance. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. The outcome measure for benefit was the proportion of polyps predicted to be nonneoplastic that would avoid removal with the use of CADx. The outcome measure for harm was the proportion of neoplastic polyps that would be not resected and left in situ due to an incorrect diagnosis with the use of CADx. Histology served as the reference standard for both outcomes. Data Synthesis: Ten studies, including 3620 patients with 4103 small rectosigmoid polyps, were analyzed. The studies that assessed the standalone performance of CADx (9 studies; 3237 polyps) showed a sensitivity of 87.3% (95% CI, 79.2% to 92.5%) (SR) and specificity of 88.9% (CI, 81.7% to 93.5%) (SR) in predicting neoplastic change. In the studies that compared histology prediction performance before versus after CADx assistance (4 studies; 2503 polyps), there was no difference in the proportion of polyps predicted to be nonneoplastic that would avoid removal (55.4% vs. 58.4%; risk ratio [RR], 1.06 [CI, 0.96 to 1.17]; moderate-certainty evidence) or in the proportion of neoplastic polyps that would be erroneously left in situ (8.2% vs. 7.5%; RR, 0.95 [CI, 0.69 to 1.33]; moderate-certainty evidence). Limitation: The application of optical diagnosis was only simulated, potentially altering the decision-making process of the operator. Conclusion: Computer-aided diagnosis provided no incremental benefit or harm in the management of small rectosigmoid polyps during colonoscopy. Primary Funding Source: European Commission. (PROSPERO: CRD42023402197)

• Parasa, Sravanthi; Berzin, Tyler; Leggett, Cadman; Gross, Seth; Repici, Alessandro & Ahmad, Omer F. [Vis alle 23 forfattere av denne artikkelen] (2024). Consensus statements on the current landscape of artificial intelligence applications in endoscopy, addressing roadblocks, and advancing artificial intelligence in gastroenterology. Gastrointestinal Endoscopy. ISSN 0016-5107. doi: 10.1016/j.gie.2023.12.003. Fulltekst i vitenarkiv
• Hassan, Cesare; Misawa, Masashi; Rizkala, Tommy; Mori, Yuichi; Sultan, Shahnaz & Facciorusso, Antonio [Vis alle 25 forfattere av denne artikkelen] (2024). Computer-Aided Diagnosis for Leaving Colorectal Polyps In Situ A Systematic Review and Meta-analysis. Annals of Internal Medicine. ISSN 0003-4819. 177(7), s. 919–928. doi: 10.7326/M23-2865. Fulltekst i vitenarkiv
• Crainic, Ioana Popescu; Djinbachian, Roupen; Rex, Douglas K.; Barkun, Alan; Shaukat, Aasma & East, James [Vis alle 15 forfattere av denne artikkelen] (2024). Expert endoscopist assessment of colorectal polyp size using virtual scale endoscopy, visual or snare-based estimation: a prospective video-based study. Scandinavian Journal of Gastroenterology. ISSN 0036-5521. doi: 10.1080/00365521.2024.2308519. Fulltekst i vitenarkiv
• Halvorsen, Natalie Grace Mosteiro & Mori, Yuichi (2024). Cost-Effectiveness for Artificial Intelligence in Colonoscopy. Gastrointestinal Endoscopy Clinics of North America. ISSN 1052-5157. doi: 10.1016/j.giec.2024.10.008. Fulltekst i vitenarkiv
• Hassan, Cesare; Rizkala, Tommy; Mori, Yuichi; Spadaccini, Marco; Misawa, Masashi & Antonelli, Giulio [Vis alle 33 forfattere av denne artikkelen] (2024). Computer-aided diagnosis for the resect-and-discard strategy for colorectal polyps: a systematic review and meta-analysis. The Lancet Gastroenterology and Hepatology. ISSN 2468-1253. 9(11), s. 1010–1019. doi: 10.1016/S2468-1253(24)00222-X. Fulltekst i vitenarkiv
• Rizkala, Tommy; Hassan, Cesare; Mori, Yuichi; Spadaccini, Marco; Antonelli, Giulio & Dekker, Evelien [Vis alle 24 forfattere av denne artikkelen] (2024). Accuracy of Computer-aided Diagnosis in Colonoscopy Varies According to Polyp Location: A Systematic Review and Meta-analysis. Clinical Gastroenterology and Hepatology. ISSN 1542-3565. doi: 10.1016/j.cgh.2024.08.021. Fulltekst i vitenarkiv
• Halvorsen, Natalie Grace Mosteiro & Mori, Yuichi (2024). Computer-aided polyp characterization in colonoscopy: sufficient performance or not? Clinical Endoscopy (CE). ISSN 2234-2400. 57(1), s. 18–23. doi: 10.5946/ce.2023.092. Fulltekst i vitenarkiv
• Iacucci, Marietta; Santacroce, Giovanni; Zammarchi, Irene; Maeda, Yasuharu; Amor, Rocío Del & Meseguer, Pablo [Vis alle 14 forfattere av denne artikkelen] (2024). Artificial intelligence and endo-histo-omics: new dimensions of precision endoscopy and histology in inflammatory bowel disease. The Lancet Gastroenterology and Hepatology. ISSN 2468-1253. doi: 10.1016/S2468-1253(24)00053-0. Fulltekst i vitenarkiv
• Ichimasa, Katsuro; Foppa, Caterina; Kudo, Shin-Ei; Misawa, Masashi; Takashina, Yuki & Miyachi, Hideyuki [Vis alle 34 forfattere av denne artikkelen] (2024). Artificial Intelligence to Predict the Risk of Lymph Node Metastasis in T2 Colorectal Cancer. Annals of Surgery. ISSN 0003-4932. 280(5), s. 850–857. doi: 10.1097/SLA.0000000000006469. Fulltekst i vitenarkiv
• Patel, Harsh K.; Mori, Yuichi; Hassan, Cesare; Rizkala, Tommy; Radadiya, Dhruvil K. & Nathani, Piyush [Vis alle 18 forfattere av denne artikkelen] (2024). Lack of Effectiveness of Computer Aided Detection for Colorectal Neoplasia: A Systematic Review and Meta-Analysis of Nonrandomized Studies. Clinical Gastroenterology and Hepatology. ISSN 1542-3565. doi: 10.1016/j.cgh.2023.11.029. Fulltekst i vitenarkiv Vis sammendrag

  Background and Aims Benefits of computer-aided detection (CADe) in detecting colorectal neoplasia were shown in many randomized trials in which endoscopists’ behavior was strictly controlled. However, the effect of CADe on endoscopists’ performance in less-controlled setting is unclear. This systematic review and meta-analyses were aimed at clarifying benefits and harms of using CADe in real-world colonoscopy. Methods We searched MEDLINE, EMBASE, Cochrane, and Google Scholar from inception to August 20, 2023. We included nonrandomized studies that compared the effectiveness between CADe-assisted and standard colonoscopy. Two investigators independently extracted study data and quality. Pairwise meta-analysis was performed utilizing risk ratio for dichotomous variables and mean difference (MD) for continuous variables with a 95% confidence interval (CI). Results Eight studies were included, comprising 9782 patients (4569 with CADe and 5213 without CADe). Regarding benefits, there was a difference in neither adenoma detection rate (44% vs 38%; risk ratio, 1.11; 95% CI, 0.97 to 1.28) nor mean adenomas per colonoscopy (0.93 vs 0.79; MD, 0.14; 95% CI, –0.04 to 0.32) between CADe-assisted and standard colonoscopy, respectively. Regarding harms, there was no difference in the mean non-neoplastic lesions per colonoscopy (8 studies included for analysis; 0.52 vs 0.47; MD, 0.14; 95% CI, –0.07 to 0.34) and withdrawal time (6 studies included for analysis; 14.3 vs 13.4 minutes; MD, 0.8 minutes; 95% CI, –0.18 to 1.90). There was a substantial heterogeneity, and all outcomes were graded with a very low certainty of evidence. Conclusion CADe in colonoscopies neither improves the detection of colorectal neoplasia nor increases burden of colonoscopy in real-world, nonrandomized studies, questioning the generalizability of the results of randomized trials.

• Maida, Marcello; Ramai, Daryl; Mori, Yuichi; Dinis-Ribeiro, Mário; Facciorusso, Antonio & Hassan, Cesare [Vis alle 25 forfattere av denne artikkelen] (2024). The role of generative language systems in increasing patient awareness of colon cancer screening. Endoscopy. ISSN 0013-726X. doi: 10.1055/a-2388-6084. Fulltekst i vitenarkiv
• Antonelli, Giulio; Libanio, Diogo; Groof, Albert Jeroen De; Sommen, Fons van der; Mascagni, Pietro & Sinonquel, Pieter [Vis alle 32 forfattere av denne artikkelen] (2024). QUAIDE - Quality assessment of AI preclinical studies in diagnostic endoscopy. Gut. ISSN 0017-5749. doi: 10.1136/gutjnl-2024-332820. Fulltekst i vitenarkiv
• Djinbachian, Roupen; Rex, Douglas K.; Chiu, Han-Mo; Fukami, Norio; Aihara, Hiroyuki & Bastiaansen, Barbara A. J. [Vis alle 49 forfattere av denne artikkelen] (2024). International consensus on the management of large (≥20 mm) colorectal laterally spreading tumors: World Endoscopy Organization Delphi study. Digestive Endoscopy. ISSN 0915-5635. doi: 10.1111/den.14826. Fulltekst i vitenarkiv
• Takashina, Yuki; Kudo, Shin-ei; Kouyama, Yuta; Ichimasa, Katsuro; Miyachi, Hideyuki & Mori, Yuichi [Vis alle 17 forfattere av denne artikkelen] (2023). Whole slide image-based prediction of lymph node metastasis in T1 colorectal cancer using unsupervised artificial intelligence. Digestive Endoscopy. ISSN 0915-5635. doi: 10.1111/den.14547. Fulltekst i vitenarkiv
• Bretthauer, Michael; Gerke, Sara; Hassan, Cesare; Ahmad, Omer F. & Mori, Yuichi (2023). The New European Medical Device Regulation: Balancing Innovation and Patient Safety. Annals of Internal Medicine. ISSN 0003-4819. 176(6), s. 844–848. doi: 10.7326/M23-0454. Fulltekst i vitenarkiv Vis sammendrag

  The European Union has introduced stricter provisions for medical devices under the new Medical Device Regulation (MDR). The MDR increases requirements for clinical trial testing for many devices before they can legally be placed on the market and extends requirements for rigorous clinical surveillance of benefits and harms to the entire life cycle of devices. New “expert panels” have been established by the European Commission to advise in the assessment of devices toward certification, and the role of previous “notified bodies” (private companies charged by the Commission with ensuring that manufacturers follow the requirements for device testing) is being expanded. The MDR does not contain a grandfathering clause; thus, all existing medical devices must be recertified under the stricter regulation. The recertification deadline has recently been extended to 2027 or 2028, depending on the device's risk class. Whether most device manufacturers can meet these new requirements is uncertain, and the MDR will likely have important consequences for manufacturers, researchers, clinicians, and patients. Enhanced collaborations between the medical device industry and physician partners will be needed to meet the new requirements in a timely manner to avoid shortages of existing devices and to mitigate barriers to development of new devices.

• Maeda, Yasuharu; Kudo, Shin-Ei; Ogata, Noriyuki; Kuroki, Takanori; Takashina, Yuki & Takishima, Kazumi [Vis alle 16 forfattere av denne artikkelen] (2023). USE OF ADVANCED ENDOSCOPIC TECHNOLOGY FOR OPTICAL CHARACTERIZATION OF NEOPLASIA IN PATIENTS WITH ULCERATIVE COLITIS: SYSTEMATIC REVIEW. Gastroenterological Endoscopy. ISSN 0387-1207. 65(9), s. 1464–1478. doi: 10.11280/gee.65.1464. Fulltekst i vitenarkiv
• Mori, Yuichi; Jin, Eun Hyo & Lee, Dongheon (2023). Enhancing artificial intelligence-doctor collaboration for computer-aided diagnosis in colonoscopy through improved digital literacy. Digestive and Liver Disease. ISSN 1590-8658. doi: 10.1016/j.dld.2023.11.033. Fulltekst i vitenarkiv
• Spadaccini, Marco; Massimi, Davide; Mori, Yuichi; Alfarone, Ludovico; Fugazza, Alessandro & Maselli, Roberta [Vis alle 10 forfattere av denne artikkelen] (2023). Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening. Diagnostics (Basel). 13(6). doi: 10.3390/diagnostics13061102. Fulltekst i vitenarkiv
• Halvorsen, Natalie Grace Mosteiro & Mori, Yuichi (2023). Artificial intelligence and upper gastrointestinal endoscopy: what is the optimal study design? Minerva Surgery. ISSN 2724-5438. 78(1). doi: 10.23736/S2724-5691.22.09810-0. Fulltekst i vitenarkiv
• Hassan, Cesare; Piovani, Daniele; Spadaccini, Marco; Parigi, Tommaso; Khalaf, Kareem & Facciorusso, Antonio [Vis alle 14 forfattere av denne artikkelen] (2023). Variability in adenoma detection rate in control groups of randomized colonoscopy trials: a systematic review and meta-analysis. Gastrointestinal Endoscopy. ISSN 0016-5107. 97(2), s. 212–225.e7. doi: 10.1016/j.gie.2022.10.009. Fulltekst i vitenarkiv
• Jiang, Kai; Itoh, Hayato; Oda, Masahiro; Okumura, Taishi; Mori, Yuichi & Misawa, Masashi [Vis alle 9 forfattere av denne artikkelen] (2023). Gaussian affinity and GIoU-based loss for perforation detection and localization from colonoscopy videos. International Journal of Computer Assisted Radiology and Surgery. ISSN 1861-6410. 18(5), s. 795–805. doi: 10.1007/s11548-022-02821-x. Fulltekst i vitenarkiv
• Bretthauer, Michael; Wieszczy, Paulina; Løberg, Magnus; Kamiński, Michał Filip; Werner, Tarjei Fiskergård & Helsingen, Lise Mørkved [Vis alle 10 forfattere av denne artikkelen] (2023). Estimated Lifetime Gained with Cancer Screening Tests: A Meta-Analysis of Randomized Clinical Trials. JAMA Internal Medicine. ISSN 2168-6106. 183(11), s. 1196–1203. doi: 10.1001/jamainternmed.2023.3798. Fulltekst i vitenarkiv
• Hassan, Cesare; Spadaccini, Marco; Mori, Yuichi; Foroutan, Farid; Facciorusso, Antonio & Gkolfakis, Paraskevas [Vis alle 23 forfattere av denne artikkelen] (2023). Real-Time Computer-Aided Detection of Colorectal Neoplasia During Colonoscopy : A Systematic Review and Meta-analysis. Annals of Internal Medicine. ISSN 0003-4819. 176(9), s. 1209–1220. doi: 10.7326/M22-3678. Fulltekst i vitenarkiv
• Spadaccini, Marco; Rondonotti, Emanuele; Radaelli, Franco; Mori, Yuichi; Hassan, Cesare & Repici, Alessandro (2023). Colonoscopy setting and impact on statistical significance in Artificial Intelligence trials. Endoscopy. ISSN 0013-726X. 55(12), s. 1151–1151. doi: 10.1055/a-2131-3315. Fulltekst i vitenarkiv
• Spadaccini, Marco; Hassan, Cesare; Rondonotti, Emanuele; Antonelli, Giulio; Andrisani, Gianluca & Lollo, Gianluca [Vis alle 40 forfattere av denne artikkelen] (2023). Combination of Mucosa-Exposure Device and Computer-Aided Detection for Adenoma Detection During Colonoscopy: A Randomized Trial. Gastroenterology. ISSN 0016-5085. 165(1), s. 244–251. doi: 10.1053/j.gastro.2023.03.237. Fulltekst i vitenarkiv
• Barua, Ishita; Misawa, Masashi; Brown, Jeremy R. Glissen; Walradt, Trent; Kudo, Shin-ei & Sheth, Sunil G. [Vis alle 19 forfattere av denne artikkelen] (2022). Speedometer for withdrawal time monitoring during colonoscopy: a clinical implementation trial. Scandinavian Journal of Gastroenterology. ISSN 0036-5521. doi: 10.1080/00365521.2022.2154616. Fulltekst i vitenarkiv
• Mori, Yuichi; Misawa, Masashi; Bernal, Jorge; Bretthauer, Michael; Kudo, Shin-ei & Rastogi, Amit [Vis alle 7 forfattere av denne artikkelen] (2022). Artificial intelligence for disease diagnosis: the criterion standard challenge. Gastrointestinal Endoscopy. ISSN 0016-5107. 96(2), s. 370–372. doi: 10.1016/j.gie.2022.04.057. Fulltekst i vitenarkiv
• Messmann, Helmut; Ebigbo, Alanna; Hassan, Cesare; Repici, Alessandro & Mori, Yuichi (2022). How to Integrate Artificial Intelligence in Gastrointestinal Practice. Gastroenterology. ISSN 0016-5085. 162(6), s. 1583–1586. doi: 10.1053/j.gastro.2022.02.029. Fulltekst i vitenarkiv
• Barua, Ishita; Wieszczy, Paulina; Kudo, Shin-ei; Masashi, Misawa; Holme, Øyvind & Gulati, Shraddha [Vis alle 34 forfattere av denne artikkelen] (2022). Real-Time Artificial Intelligence–Based Optical Diagnosis of Neoplastic Polyps during Colonoscopy. NEJM Evidence. 1(6). doi: 10.1056/EVIDoa2200003. Fulltekst i vitenarkiv
• Ishiyama, Misaki; Kudo, Shin-ei; Misawa, Masashi; Mori, Yuichi; Maeda, Yasuhara & Ichimasa, Katsuro [Vis alle 14 forfattere av denne artikkelen] (2022). Impact of the clinical use of artificial intelligence–assisted neoplasia detection for colonoscopy: a large-scale prospective, propensity score–matched study (with video). Gastrointestinal Endoscopy. ISSN 0016-5107. 95(1), s. 155–163. doi: 10.1016/j.gie.2021.07.022. Fulltekst i vitenarkiv Vis sammendrag

  Background and Aims Recently, the use of computer-aided detection (CADe) for colonoscopy has been investigated to improve the adenoma detection rate (ADR). We aimed to assess the efficacy of a regulatory-approved CADe in a large-scale study with high numbers of patients and endoscopists. Methods This was a propensity score–matched prospective study that took place at a university hospital between July 2020 and December 2020. We recruited patients aged ≥20 years who were scheduled for colonoscopy. Patients with polyposis, inflammatory bowel disease, or incomplete colonoscopy were excluded. We used a regulatory-approved CADe system and conducted a propensity score matching–based comparison of the ADR between patients examined with and without CADe as the primary outcome. Results During the study period, 2261 patients underwent colonoscopy with the CADe system or routine colonoscopy, and 172 patients were excluded in accordance with the exclusion criteria. Thirty endoscopists (9 nonexperts and 21 experts) were involved in this study. Propensity score matching was conducted using 5 factors, resulting in 1836 patients included in the analysis (918 patients in each group). The ADR was significantly higher in the CADe group than in the control group (26.4% vs 19.9%, respectively; relative risk, 1.32; 95% confidence interval, 1.12-1.57); however, there was no significant increase in the advanced neoplasia detection rate (3.7% vs 2.9%, respectively). Conclusions The use of the CADe system for colonoscopy significantly increased the ADR in a large-scale prospective study including 30 endoscopists (Clinical trial registration number: UMIN000040677.)

• Ainechi, Diba; Misawa, Masashi; Barua, Ishita; Larsen, Solveig; Paulsen, Vemund & Garborg, Kjetil Kjeldstad [Vis alle 21 forfattere av denne artikkelen] (2022). Impact of artificial intelligence on colorectal polyp detection for early-career endoscopists: an international comparative study. Scandinavian Journal of Gastroenterology. ISSN 0036-5521. doi: 10.1080/00365521.2022.2070436. Fulltekst i vitenarkiv Vis sammendrag

  Background Artificial intelligence (AI) for polyp detection is being introduced to colonoscopy, but there is uncertainty how this affects endoscopists’ ability to detect polyps and neoplasms. We performed a video-based study to address whether AI improved the endoscopists’ performance to detect polyps. Methods We established a dataset of 200 colonoscopy videos (length 5 s; 100 without polyps and 100 with one polyp). About 33 early-career endoscopists (50–400 colonoscopies performed) from 10 European countries classified each video as either ‘polyp present’ or ‘polyp not present’. The video assessment was performed twice with a four-week interval. The first assessment was performed without any AI tool, whereas the second was performed with an AI tool for polyp detection. The primary endpoint was early-career endoscopists’ sensitivity to detect polyps. Gold standard for presence and histology of polyps were confirmed by two expert endoscopists and pathologists, respectively. McNemar’s test was used for statistical significance. Results There were 86 neoplastic and 14 non-neoplastic polyps (mean size 5.6 mm) in the 100 videos with polyps. Early-career endoscopists’ sensitivity to detect polyps increased from 86.3% (95% confidence interval [CI]: 85.1–87.5%) to 91.7% (95%CI: 90.7–92.6%) with the AI aid (p < .0001). Their sensitivity to detect neoplastic polyps increased from 85.4% (95% CI: 84.0–86.7%) to 92.1% (95%CI: 91.1–93.1%) with the AI aid (p < .0001). Conclusion The polyp detection AI tool helped early-career endoscopists to increase their sensitivity to identify all polyps and neoplastic polyps during colonoscopy.

• Itoh, Hayato; Misawa, Masashi; Mori, Yuichi; Kudo, Shin-Ei; Oda, Masahiro & Mori, Kensaku (2022). Positive-gradient-weighted object activation mapping: visual explanation of object detector towards precise colorectal-polyp localisation. International Journal of Computer Assisted Radiology and Surgery. ISSN 1861-6410. doi: 10.1007/s11548-022-02696-y. Fulltekst i vitenarkiv
• Pecere, Silvia; Antonelli, Giulio; Dinis-Ribeiro, Mario; Mori, Yuichi; Hassan, Cesare & Fuccio, Lorenzo [Vis alle 20 forfattere av denne artikkelen] (2022). Endoscopists performance in optical diagnosis of colorectal polyps in artificial intelligence studies. United European Gastroenterology Journal (UEG Journal). ISSN 2050-6406. 10(8), s. 817–826. doi: 10.1002/ueg2.12285. Fulltekst i vitenarkiv
• Areia, Miguel; Mori, Yuichi; Correale, Loredana; Repici, Alessandro; Bretthauer, Michael & Sharma, Prateek [Vis alle 18 forfattere av denne artikkelen] (2022). Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study. The Lancet Digital Health. 4(6), s. e436–e444. doi: 10.1016/S2589-7500(22)00042-5. Fulltekst i vitenarkiv Vis sammendrag

  Background Artificial intelligence (AI) tools increase detection of precancerous polyps during colonoscopy and might contribute to long-term colorectal cancer prevention. The aim of the study was to investigate the incremental effect of the implementation of AI detection tools in screening colonoscopy on colorectal cancer incidence and mortality, and the cost-effectiveness of such tools. Methods We conducted Markov model microsimulation of using colonoscopy with and without AI for colorectal cancer screening for individuals at average risk (no personal or family history of colorectal cancer, adenomas, inflammatory bowel disease, or hereditary colorectal cancer syndrome). We ran the microsimulation in a hypothetical cohort of 100 000 individuals in the USA aged 50–100 years. The primary analysis investigated screening colonoscopy with versus without AI every 10 years starting at age 50 years and finishing at age 80 years, with follow-up until age 100 years, assuming 60% screening population uptake. In secondary analyses, we modelled once-in-life screening colonoscopy at age 65 years in adults aged 50–79 years at average risk for colorectal cancer. Post-polypectomy surveillance followed the simplified current guideline. Costs of AI tools and cost for downstream treatment of screening detected disease were estimated with 3% annual discount rates. The main outcome measures included the incremental effect of AI-assisted colonoscopy versus standard (no-AI) colonoscopy on colorectal cancer incidence and mortality, and cost-effectiveness of screening projected for the average risk screening US population. Findings In the primary analyses, compared with no screening, the relative reduction of colorectal cancer incidence with screening colonoscopy without AI tools was 44·2% and with screening colonoscopy with AI tools was 48·9% (4·8% incremental gain). Compared with no screening, the relative reduction in colorectal cancer mortality with screening colonoscopy with no AI was 48·7% and with screening colonoscopy with AI was 52·3% (3·6% incremental gain). AI detection tools decreased the discounted costs per screened individual from $3400 to $3343 (a saving of $57 per individual). Results were similar in the secondary analyses modelling once-in-life colonoscopy. At the US population level, the implementation of AI detection during screening colonoscopy resulted in yearly additional prevention of 7194 colorectal cancer cases and 2089 related deaths, and a yearly saving of US$290 million. Interpretation Our findings suggest that implementation of AI detection tools in screening colonoscopy is a cost-saving strategy to further prevent colorectal cancer incidence and mortality. Funding European Commission and Japan Society of Promotion of Science.

• Rex, Douglas K.; Mori, Yuichi; Sharma, Prateek; Lahr, Rachel E.; Vemulapalli, Krishna C. & Hassan, Cesare (2022). Strengths and Weaknesses of an Artificial Intelligence Polyp Detection Program as Assessed by a High-Detecting Endoscopist. Gastroenterology. ISSN 0016-5085. 163(2), s. 354–358.e1. doi: 10.1053/j.gastro.2022.03.055. Fulltekst i vitenarkiv
• Ichimasa, Katsuro; Nakahara, Kenta; Kudo, Shin-ei; Misawa, Masashi; Bretthauer, Michael & Shimada, Shoji [Vis alle 14 forfattere av denne artikkelen] (2022). Novel “resect and analysis” approach for T2 colorectal cancer with use of artificial intelligence. Gastrointestinal Endoscopy. ISSN 0016-5107. 96(4), s. 665–672.e1. doi: 10.1016/j.gie.2022.04.1305. Fulltekst i vitenarkiv
• Mori, Yuichi (2022). Optimising endoscopy practice with artificial intelligence. Gastrointestinal nursing. ISSN 1479-5248. doi: 10.12968/gasn.2022.20.Sup8.S6. Fulltekst i vitenarkiv
• Hassan, Cesare; Mori, Yuichi; Sharma, Prateek; Spadaccini, Marco & Repici, Alessandro (2022). Detrimental Detection of Advanced Lesions With AI: False Confidence or Prevalence Bias? American Journal of Gastroenterology. ISSN 0002-9270. 117(12), s. 2088–2089. doi: 10.14309/ajg.0000000000002023. Fulltekst i vitenarkiv
• Barua, Ishita; Bretthauer, Michael & Mori, Yuichi (2022). Computer-aided quality assessment (CAQ): the next step for artificial intelligence in colonoscopy? Mini-invasive Surgery. 6. doi: 10.20517/2574-1225.2022.05. Fulltekst i vitenarkiv
• Spadaccini, Marco; Hassan, Cesare; Alfarone, Ludovico; Rio, Leonardo Da; Maselli, Roberta & Carrara, Silvia [Vis alle 16 forfattere av denne artikkelen] (2022). Comparing the number and relevance of false activations between 2 artificial intelligence computer-aided detection systems: the NOISE study. Gastrointestinal Endoscopy. ISSN 0016-5107. 95(5), s. 975–981.e1. doi: 10.1016/j.gie.2021.12.031. Fulltekst i vitenarkiv
• Mori, Yuichi; Wang, Pu; Løberg, Magnus; Misawa, Masashi; Repici, Alessandro & Spadaccini, Marco [Vis alle 26 forfattere av denne artikkelen] (2022). Impact of Artificial Intelligence on Colonoscopy Surveillance After Polyp Removal: A Pooled Analysis of Randomized Trials. Clinical Gastroenterology and Hepatology. ISSN 1542-3565. doi: 10.1016/j.cgh.2022.08.022. Fulltekst i vitenarkiv Vis sammendrag

  Background and Aims Artificial intelligence (AI) tools aimed at improving polyp detection have been shown to increase the adenoma detection rate during colonoscopy. However, it is unknown how increased polyp detection rates by AI affect the burden of patient surveillance after polyp removal. Methods We conducted a pooled analysis of 9 randomized controlled trials (5 in China, 2 in Italy, 1 in Japan, and 1 in the United States) comparing colonoscopy with or without AI detection aids. The primary outcome was the proportion of patients recommended to undergo intensive surveillance (ie, 3-year interval). We analyzed intervals for AI and non-AI colonoscopies for the U.S. and European recommendations separately. We estimated proportions by calculating relative risks using the Mantel-Haenszel method. Results A total of 5796 patients (51% male, mean 53 years of age) were included; 2894 underwent AI-assisted colonoscopy and 2902 non-AI colonoscopy. When following U.S. guidelines, the proportion of patients recommended intensive surveillance increased from 8.4% (95% CI, 7.4%–9.5%) in the non-AI group to 11.3% (95% CI, 10.2%–12.6%) in the AI group (absolute difference, 2.9% [95% CI, 1.4%–4.4%]; risk ratio, 1.35 [95% CI, 1.16–1.57]). When following European guidelines, it increased from 6.1% (95% CI, 5.3%–7.0%) to 7.4% (95% CI, 6.5%–8.4%) (absolute difference, 1.3% [95% CI, 0.01%–2.6%]; risk ratio, 1.22 [95% CI, 1.01–1.47]). Conclusions The use of AI during colonoscopy increased the proportion of patients requiring intensive colonoscopy surveillance by approximately 35% in the United States and 20% in Europe (absolute increases of 2.9% and 1.3%, respectively). While this may contribute to improved cancer prevention, it significantly adds patient burden and healthcare costs.

• Itoh, Hayato; Oda, Masahiro; Jiang, Kai; Mori, Yuichi; Misawa, Masashi & Kudo, Shin-Ei [Vis alle 10 forfattere av denne artikkelen] (2022). Uncertainty meets 3D-spatial feature in colonoscopic polyp-size determination. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization. ISSN 2168-1163. 10(3). doi: 10.1080/21681163.2021.2004445. Fulltekst i vitenarkiv
• Larsen, Solveig Linnea Veen & Mori, Yuichi (2022). Artificial intelligence in colonoscopy: A review on the current status. DEN Open. 2(1). doi: 10.1002/deo2.109. Fulltekst i vitenarkiv
• Messmann, Helmut; Bisschops, Raf; Antonelli, Giulio; Libânio, Diogo; Sinonquel, Pieter & Abdelrahim, Mohamed [Vis alle 33 forfattere av denne artikkelen] (2022). Expected value of artificial intelligence in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement. Endoscopy. ISSN 0013-726X. 54(12), s. 1211–1231. doi: 10.1055/a-1950-5694. Fulltekst i vitenarkiv
• Ichimasa, Katsuro; Kudo, Shin-Ei; Miyachi, Hideyuki; Kouyama, Yuta; Misawa, Masashi & Mori, Yuichi (2021). Risk stratification of T1 colorectal cancer metastasis to Lymph nodes: Current status and perspective. Gut and Liver. ISSN 1976-2283. 15(6), s. 818–826. doi: 10.5009/gnl20224. Fulltekst i vitenarkiv
• Kudo, Shin-Ei; Ichimasa, Katsuro; Villard, Benjamin; Mori, Yuichi; Misawa, Masashi & Saito, Shoichi [Vis alle 29 forfattere av denne artikkelen] (2021). Artificial Intelligence System to Determine Risk of T1 Colorectal Cancer Metastasis to Lymph Node. Gastroenterology. ISSN 0016-5085. 160(4), s. 1075–1084.e2. doi: 10.1053/j.gastro.2020.09.027. Fulltekst i vitenarkiv
• Helsingen, Lise Mørkved; Løberg, Magnus; Refsum, Erle; Gjøstein, Dagrun Kyte; Wieszczy, Paulina & Olsvik, Ørjan [Vis alle 16 forfattere av denne artikkelen] (2021). Covid-19 transmission in fitness centers in Norway - a randomized trial. BMC Public Health. 21, s. 1–9. doi: 10.1186/s12889-021-12073-0. Fulltekst i vitenarkiv Vis sammendrag

  Background: Closed fitness centers during the Covid-19 pandemic may negatively impact health and wellbeing. We assessed whether training at fitness centers increases the risk of SARS-CoV-2 virus infection.<p> <p>Methods: In a two-group parallel randomized controlled trial, fitness center members aged 18 to 64 without Covid-19-relevant comorbidities, were randomized to access to training at a fitness center or no-access. Fitness centers applied physical distancing (1 m for floor exercise, 2 m for high-intensity classes) and enhanced hand and surface hygiene. Primary outcomes were SARS-CoV-2 RNA status by polymerase chain reaction (PCR) after 14 days, hospital admission after 21 days. The secondary endpoint was SARS-CoV-2 antibody status after 1 month.<p> <p>Results: 3764 individuals were randomized; 1896 to the training arm and 1868 to the no-training arm. In the training arm, 81.8% trained at least once, and 38.5% trained ≥six times. Of 3016 individuals who returned the SARSCoV-2 RNA tests (80.5%), there was one positive test in the training arm, and none in the no-training arm (risk difference 0.053%; 95% CI − 0.050 to 0.156%; p = 0.32). Eleven individuals in the training arm (0.8% of tested) and 27 in the no-training arm (2.4% of tested) tested positive for SARS-CoV-2 antibodies (risk difference − 0.87%; 95%CI − 1.52% to − 0.23%; p = 0.001). No outpatient visits or hospital admissions due to Covid-19 occurred in either arm.<p> <p>Conclusion: Provided good hygiene and physical distancing measures and low population prevalence of SARS-CoV-2 infection, there was no increased infection risk of SARS-CoV-2 in fitness centers in Oslo, Norway for individuals without Covid-19-relevant comorbidities.

• Mori, Yuichi; Kudo, Shin-Ei; East, James; Rastogi, Amit; Bretthauer, Michael & Misawa, Masashi [Vis alle 14 forfattere av denne artikkelen] (2020). Cost savings in colonoscopy with artificial intelligence-aided polyp diagnosis: an add-on analysis of a clinical trial (with video). Gastrointestinal Endoscopy. ISSN 0016-5107. 92(4), s. 905–911. doi: 10.1016/j.gie.2020.03.3759. Fulltekst i vitenarkiv
• Barua, Ishita; Mori, Yuichi & Bretthauer, Michael (2020). Colorectal polyp characterization with endocytoscopy: Ready for widespread implementation with artificial intelligence? Baillière's Best Practice & Research Clinical Gastroenterology. ISSN 1521-6918. doi: 10.1016/j.bpg.2020.101721. Fulltekst i vitenarkiv

Se alle arbeider i NVA

• Mori, Yuichi (2024). Artificial intelligence for a rare disease. Endoscopy. ISSN 0013-726X. doi: 10.1055/a-2487-1252. Fulltekst i vitenarkiv
• Mori, Yuichi (2024). New horizons in polyp size estimation. Endoscopy. ISSN 0013-726X. doi: 10.1055/a-2224-0756. Fulltekst i vitenarkiv
• Mori, Yuichi; East, James E.; Hassan, Cesare; Halvorsen, Natalie Grace Mosteiro; Berzin, Tyler M. & Byrne, Michael [Vis alle 25 forfattere av denne artikkelen] (2023). BENEFITS AND CHALLENGES IN IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE IN COLONOSCOPY: WORLD ENDOSCOPY ORGANIZATION POSITION STATEMENT. Gastroenterological Endoscopy. ISSN 0387-1207. 65(10), s. 2231–2241. doi: 10.11280/gee.65.2231. Fulltekst i vitenarkiv
• Bretthauer, Michael; Mori, Yuichi; Zessner-Spitzenberg, Jasmin; Kamiński, Michał F.; Siersema, Peter D. & Ponchon, Thierry [Vis alle 10 forfattere av denne artikkelen] (2023). Gastrointestinal endoscopy devices and the European Union Medical Device Regulation: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement. Endoscopy. ISSN 0013-726X. 55(6), s. 578–581. doi: 10.1055/a-2052-2540. Fulltekst i vitenarkiv
• Hassan, Cesare; Mori, Yuichi & Sharma, Prateek (2023). The Pros and Cons of Artificial Intelligence in Endoscopy. American Journal of Gastroenterology. ISSN 0002-9270. 118(10), s. 1720–1722. doi: 10.14309/ajg.0000000000002287. Fulltekst i vitenarkiv
• Hassan, Cesare; Repici, Alessandro & Mori, Yuichi (2023). Cost of artificial intelligence: Elephant in the room and its cage. Digestive Endoscopy. ISSN 0915-5635. doi: 10.1111/den.14567. Fulltekst i vitenarkiv
• Jiang, Kai; Itoh, Hayato; Oda, Masahiro; Okumura, Taishi; Mori, Yuichi & Misawa, Masashi [Vis alle 9 forfattere av denne artikkelen] (2023). Correction to: Gaussian affinity and GIoU-based loss for perforation detection and localization from colonoscopy videos (International Journal of Computer Assisted Radiology and Surgery, (2023), 18, 5, (795-805), 10.1007/s11548-022-02821-x). International Journal of Computer Assisted Radiology and Surgery. ISSN 1861-6410. 18(5), s. 807–807. doi: 10.1007/s11548-023-02899-x. Fulltekst i vitenarkiv
• Mori, Yuichi; East, James E.; Hassan, Cesare; Halvorsen, Natalie Grace Mosteiro; Berzin, Tyler M. & Byrne, Michael [Vis alle 25 forfattere av denne artikkelen] (2023). Benefits and challenges in implementation of artificial intelligence in colonoscopy: World Endoscopy Organization position statement. Digestive Endoscopy. ISSN 0915-5635. s. 1–8. doi: 10.1111/den.14531. Fulltekst i vitenarkiv
• Halvorsen, Natalie Grace Mosteiro & Mori, Yuichi (2022). Open access database for artificial intelligence research. Gastrointestinal Endoscopy. ISSN 0016-5107. 97(2), s. 200–201. doi: 10.1016/j.gie.2022.10.020. Fulltekst i vitenarkiv
• Rex, Douglas K.; Berzin, Tyler M. & Mori, Yuichi (2022). Artificial Intelligence Improves Detection at Colonoscopy: Why Aren't We All Already Using It? Gastroenterology. ISSN 0016-5085. 163(1), s. 35–37. doi: 10.1053/j.gastro.2022.04.042. Fulltekst i vitenarkiv
• Ichimasa, Katsuro; Kudo, Shin-ei; Koh, Calvin Jianyi; Yeoh, Khay Guan & Mori, Yuichi (2022). Endoscopic full-thickness resection for complex colorectal lesions–what’s the next step? Scandinavian Journal of Gastroenterology. ISSN 0036-5521. doi: 10.1080/00365521.2022.2089858. Fulltekst i vitenarkiv
• Saito, Yutaka; Yamada, Masayoshi & Mori, Yuichi (2022). Although depth prediction of colorectal cancer with artificial intelligence is clinically relevant, standardization of histopathologic diagnosis should also be taken care of. Gastrointestinal Endoscopy. ISSN 0016-5107. 95(6), s. 1195–1197. doi: 10.1016/j.gie.2022.02.008. Fulltekst i vitenarkiv
• Hassan, Cesare; Mori, Yuichi & Repici, Alessandro (2022). Commentary. Endoscopy. ISSN 0013-726X. 54(5), s. 521–521. doi: 10.1055/a-1736-8097. Fulltekst i vitenarkiv
• Ahuja, Amisha & Mori, Yuichi (2022). High-quality Studies of Artificial Intelligence in Colonoscopy Illuminate a Next Important Step. Gastroenterology. ISSN 0016-5085. 163(3), s. 582–583. doi: 10.1053/j.gastro.2022.06.074. Fulltekst i vitenarkiv
• Frazzoni, Leonardo; Arribas, Julia; Antonelli, Giulio; Libanio, Diogo; Ebigbo, Alanna & Sommen, Fons Van Der [Vis alle 20 forfattere av denne artikkelen] (2022). Erratum: Endoscopists' diagnostic accuracy in detecting upper gastrointestinal neoplasia in the framework of artificial intelligence studies (Endoscopy (2022) 54 (403-411) DOI: 10.1055/a-1500-3730). Endoscopy. ISSN 0013-726X. 54(4), s. C12–C12. doi: 10.1055/a-1907-9242. Fulltekst i vitenarkiv
• Mori, Yuichi; Kamiński, Michał Filip; Hassan, Cecare & Bretthauer, Michael (2022). Clinical trial designs for artificial intelligence in gastrointestinal endoscopy. The Lancet Gastroenterology and Hepatology. ISSN 2468-1253. doi: 10.1016/S2468-1253(22)00232-1. Fulltekst i vitenarkiv
• Mori, Yuichi; Misawa, Masashi & Kudo, Shin-ei (2022). Challenges in artificial intelligence for polyp detection. Digestive Endoscopy. ISSN 0915-5635. doi: 10.1111/den.14279. Fulltekst i vitenarkiv
• Norum, Maria; Viken, Jonas; Torgersen, Gard Elias Østlie; Stubhaug, Olav Eliasson; Buric, Nadja & Svartsund, Maren Flø [Vis alle 8 forfattere av denne artikkelen] (2026). «Må det gjøre så vondt?» Topikal smertelindring ved spiralinnsetting. Universitetet i Oslo. Fulltekst i vitenarkiv
• Selina, Anna; Sandstø, Vihtari; Resheed, Bryar Sherzad; Shirazi, Dena; Madadgar, Helia & Dormagen, Lea Taraldsrud [Vis alle 8 forfattere av denne artikkelen] (2026). Håndtering av røykeksponerte pasienter på Oslo legevakt. Universitetet i Oslo. Fulltekst i vitenarkiv
• Almehagen, Nora; Tveitan, Per Gavle; Koistinaho, Aura; Dareez, Jasmin Deeba; Bøe, Ine & Uthayakumar, Tivani [Vis alle 8 forfattere av denne artikkelen] (2026). Unngå bildediagnostikk ved ukomplisert hodepine uten varselsymptomer på Radiologisk Avdeling ved Drammen Sykehus. Universitetet i Oslo. Fulltekst i vitenarkiv Vis sammendrag

  Tema Prosjektet vårt baserer seg på en anbefaling fra Legeforeningens “Kloke valg”-kampanje, som omhandler å unngå bildediagnostikk ved ukomplisert hodepine uten varselsymptomer. Etter ønske fra Radiologisk avdeling på Drammen sykehus tar oppgaven for seg i CT caput hos disse pasientene i en vaktsetting. Temaet for oppgaven er å undersøke kunnskapsgrunnlaget rundt CT-caput ved ukomplisert hodepine uten varselsymptomer, samt kritisk vurdering av kunnskapsgrunnlaget bak “Kloke valg”-kampanjens anbefaling. Kunnskapsgrunnlag Kunnskapsgrunnlaget vårt bygger på en artikkel fra UpToDate, som tar for seg voksne pasienter med ikke-traumatisk hodepine i akuttmottak. Både artikkelen og de enkelte artiklene som den er basert på er kritisk vurdert gjennom sjekklister og gjennomlesning. Vi fant at bildediagnostikk hos pasienter med ukomplisert hodepine uten varselsymptomer viser funn forenlig med alvorlig patologi i 2,4% av tilfellene, og at det derfor ikke anbefales bildediagnostikk av disse pasientene. En studie fant også at 9,6% reduksjon i bruk av CT caput hos hodepinepasienter ikke førte til økt dødelighet eller redusert oppdagelse av intrakranielle diagnoser. Alle tilgrunnliggende artikler bak “Kloke valg”-kampanjens anbefaling er også kritisk vurdert på samme måte, og samsvarer med UpToDate sin konklusjon. Vi har ikke lyktes å finne nasjonale retningslinjer om temaet. Tiltak Tiltakene våre er innføring av flytskjema for vurdering av hodepine og undervisning for legene i akuttmottaket. Gjennomføringen av disse kan måles med kvalitetsindikatorer som ser på antall CT caput, antall CT caput med funn, og hvor stor andel av legene som har hatt opplæring. Ledelse og organisering For å gjennomføre prosjektet må det opprettes en arbeidsgruppe som inkluderer personer fra ulike berørte fagområder som radiologi, akutt- og mottaksmedisin, indremedisin, men også pasientkoordinator og representant fra ledelsen. Noe av motstanden som forventes er bekymring for å overse alvorlig patologi ved reduksjon av bildediagnostikk, bruk av bildediagnostikk av logistiske/organisatoriske grunner eller forventning om bildediagnostikk fra henvisende lege. Dette kan håndteres med god informasjon og opplæring i riktige indikasjoner for bildediagnostikk, bruk av flytskjema og tydeliggjøring av radiologens rolle som støttespiller. Konklusjon Kloke valg-kampanjens anbefalinger støttes av den oppdaterte kunnskapen fra vårt litteratursøk, men kampanjen har behov for oppdaterte kilder. I litteraturen fant vi at pasienter med ukomplisert hodepine uten varselsymptomer rutinemessig ikke trenger CT caput i akuttmottak. For å redusere overforbruk av CT caput hos denne pasientgruppen har vi laget et kvalitetsforbedringsprosjekt for som inkluderer undervisning om riktig indikasjoner for CT caput blant LIS1, innføring av flytskjema for CT caput.

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