Learning and deskilling effects of artificial intelligence in colonoscopy among endoscopists with different levels of experience: a pragmatic, prospective trial. [PDF]
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Deep Learning-Based Computer-Aided Detection and Diagnosis System for Malignant Biliary Stricture (With Video). [PDF]
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A Controlled-Area Droplet Evaporimeter Reveals Surface Pressure-Dependent Evaporation Resistance of the Tear Film Lipid Layer. [PDF]
Invest Ophthalmol Vis SciGuo Y, Dang T, Li G, Zuo YY.
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Bridging the Precancerous Gap in Colorectal Cancer Through AI-Enhanced Liquid Biopsy, Endoscopy, and Digital Pathology. [PDF]
Cancers (Basel)Saridakis G, Mavroudis D, Souglakos J.
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From Simulations to AI: Samir Grover on How Tech Can Enhance Medical Education. [PDF]
J Med Internet ResSpichak S.
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Generative adversarial networks for balancing and expanding data resources for computer-aided detection in colonoscopy. [PDF]
Front Med Technolvan der Laan JJH +4 more
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Comments on "Artificial Intelligence in Colonoscopy Surveillance for Lynch Syndrome: Emerging Evidence, Lessons Learned From Average-Risk Populations, and Future Directions". [PDF]
Int J CancerYu Z, Xiong W, Hu H, Qin F.
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The role of artificial intelligence in adenoma detection during colonoscopy: a systematic review and meta-analysis of randomized controlled trials-Artificial intelligence and adenoma detection. [PDF]
Tech ColoproctolBananzadeh A +4 more
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Using the NASSS-Complexity Assessment Tool to Evaluate the Implementation of "Cadê O Kauê?": Chat-Story Intervention for Youth Participation in Mental Health Promotion in Brazil. [PDF]
J Med Internet ResSetia S +3 more
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