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AI colonoscopy
The imitation game: a review of the use of artificial intelligence in colonoscopy, and endoscopists’ perceptions thereof
Sarah Tham, Frederick H. Koh, Jasmine Ladlad, Koy-Min Chue, SKH Endoscopy Centre, Cui-Li Lin, Eng-Kiong Teo, Fung-Joon Foo
Ann Coloproctol. 2023;39(5):385-394.   Published online March 10, 2023
DOI: https://doi.org/10.3393/ac.2022.00878.0125
  • 8,317 View
  • 150 Download
  • 3 Web of Science
  • 3 Citations
AbstractAbstract PDF
The development of deep learning systems in artificial intelligence (AI) has enabled advances in endoscopy, and AI-aided colonoscopy has recently been ushered into clinical practice as a clinical decision-support tool. This has enabled real-time AI-aided detection of polyps with a higher sensitivity than the average endoscopist, and evidence to support its use has been promising thus far. This review article provides a summary of currently published data relating to AI-aided colonoscopy, discusses current clinical applications, and introduces ongoing research directions. We also explore endoscopists’ perceptions and attitudes toward the use of this technology, and discuss factors influencing its uptake in clinical practice.

Citations

Citations to this article as recorded by  
  • New Concept of Colonoscopy Assisted by a Microwave-Based Accessory Device: First Clinical Experience
    Oswaldo Ortiz, Oriol Sendino, Silvia Rivadulla, Alejandra Garrido, Luz María Neira, Josep Sanahuja, Pilar Sesé, Marta Guardiola, Glòria Fernández-Esparrach
    Cancers.2025; 17(7): 1073.     CrossRef
  • Deep learning model for gastrointestinal polyp segmentation
    Zitong Wang, Zeyi Wang, Pengyu Sun
    PeerJ Computer Science.2025; 11: e2924.     CrossRef
  • Does AI have utility in medical student surgical education? A comparative analysis of chatbots in answering standardized surgical multiple-choice questions
    Natalia DaFonte, Angelo Cadiente, Catherine Implicito, Natasha Becker, Burton Surick
    Global Surgical Education - Journal of the Association for Surgical Education.2025;[Epub]     CrossRef
The Future Medical Science and Colorectal Surgeons
Young Jin Kim
Ann Coloproctol. 2017;33(6):207-209.   Published online December 31, 2017
DOI: https://doi.org/10.3393/ac.2017.33.6.207
  • 5,080 View
  • 64 Download
  • 6 Web of Science
  • 7 Citations
AbstractAbstract PDF

Future medical technology breakthroughs will build from the incredible progress made in computers, biotechnology, and nanotechnology and from the information learned from the human genome. With such technology and information, computer-aided diagnoses, organ replacement, gene therapy, personalized drugs, and even age reversal will become possible. True 3-dimensional system technology will enable surgeons to envision key clinical features and will help them in planning complex surgery. Surgeons will enter surgical instructions in a virtual space from a remote medical center, order a medical robot to perform the operation, and review the operation in real time on a monitor. Surgeons will be better than artificial intelligence or automated robots when surgeons (or we) love patients and ask questions for a better future. The purpose of this paper is looking at the future medical science and the changes of colorectal surgeons.

Citations

Citations to this article as recorded by  
  • Development of artificial intelligence technology in diagnosis, treatment, and prognosis of colorectal cancer
    Feng Liang, Shu Wang, Kai Zhang, Tong-Jun Liu, Jian-Nan Li
    World Journal of Gastrointestinal Oncology.2022; 14(1): 124.     CrossRef
  • Modern Machine Learning Practices in Colorectal Surgery: A Scoping Review
    Stephanie Taha-Mehlitz, Silvio Däster, Laura Bach, Vincent Ochs, Markus von Flüe, Daniel Steinemann, Anas Taha
    Journal of Clinical Medicine.2022; 11(9): 2431.     CrossRef
  • Surgical safety in the COVID-19 era: present and future considerations
    Young Il Kim, In Ja Park
    Annals of Surgical Treatment and Research.2022; 102(6): 295.     CrossRef
  • Introducing Mobile Collaborative Robots into Bioprocessing Environments: Personalised Drug Manufacturing and Environmental Monitoring
    Robins Mathew, Robert McGee, Kevin Roche, Shada Warreth, Nikolaos Papakostas
    Applied Sciences.2022; 12(21): 10895.     CrossRef
  • 7P pediatrics — Medicine of Development and Health Programming
    Leyla S. Namazova-Baranova, Alexandr A. Baranov, Elena A. Vishneva, Anna A. Alekseeva, Valerii Y. Albitskiy, Irina A. Belyaeva, Viliya A. Bulgakova, Nato D. Vashakmadze, Olga B. Gordeeva, Irina V. Zelenkova, Elena V. Kaitukova, Georgii A. Karkashadze, Ele
    Annals of the Russian academy of medical sciences.2021; 76(6): 622.     CrossRef
  • Application and Prospect of a Mobile Hospital in Disaster Response
    Xinlin Chen, Lu Lu, Jie Shi, Xin Zhang, Haojun Fan, Bin Fan, Bo Qu, Qi Lv, Shike Hou
    Disaster Medicine and Public Health Preparedness.2020; 14(3): 377.     CrossRef
  • The effect of diets delivered into the gastrointestinal tract on gut motility after colorectal surgery—a systematic review and meta-analysis of randomised controlled trials
    Sophie Hogan, Daniel Steffens, Anna Rangan, Michael Solomon, Sharon Carey
    European Journal of Clinical Nutrition.2019; 73(10): 1331.     CrossRef
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