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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Quality assessment in endoscopy "artificial intelligence in endoscopy".

Yuchi Mori1, Masashi Misawa2

  • 1Clinical Effectiveness Research Group, University of Oslo and Oslo University Hospital, Oslo, Norway; Gastroenterology Section, Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway; Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.

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Artificial intelligence (AI) enhances endoscopy quality by improving polyp detection and workflow. AI tools offer objective improvements, reducing variability in endoscopic performance and reporting.

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Area of Science:

  • Medical Technology
  • Gastroenterology
  • Artificial Intelligence

Background:

  • Endoscopy quality varies due to endoscopist competence.
  • Artificial intelligence (AI) offers potential for objective quality improvement.

Purpose of the Study:

  • To review AI advancements in endoscopy.
  • To discuss evidence, challenges, and practical applications of AI in endoscopy.

Main Methods:

  • Review of current literature on AI in endoscopy.
  • Analysis of AI applications in colorectal and upper GI endoscopy.

Main Results:

  • AI tools assist in real-time polyp detection (CADe) and characterization (CADx).
  • AI supports colonoscopy quality assurance (CAQ) and workflow optimization.
  • AI implementation is advancing rapidly, particularly in colonoscopy.

Conclusions:

  • AI technologies are poised to standardize and enhance endoscopy quality.
  • Addressing regulatory and ethical challenges is crucial for AI maximization in clinical practice.