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Artificial Intelligence in Upper Gastrointestinal Diagnosis
Sabrina Xin Zi Quek1, Khek Yu Ho1,2
1Division of Gastroenterology and Hepatology, Department of Medicine, National University of Singapore, Singapore.
Artificial intelligence (AI) enhances upper gastrointestinal endoscopy by improving disease detection and streamlining workflows. AI tools aid in diagnosing precancerous conditions and guiding early gastric cancer therapy, optimizing patient care.
Area of Science:
- Gastroenterology
- Medical Imaging
- Artificial Intelligence
Background:
- Artificial intelligence (AI) is transforming upper gastrointestinal (GI) endoscopy.
- AI technologies like machine learning and deep learning enhance diagnostic accuracy and clinical workflows.
Purpose of the Study:
- To review the role of AI in upper GI endoscopy.
- To explore AI applications in disease detection, characterization, and management.
- To discuss challenges and future directions for AI in endoscopy.
Main Methods:
- Review of AI technologies including machine learning, deep learning, and convolutional neural networks.
- Exploration of AI applications in detecting lesions, precancerous conditions (Barrett's esophagus, atrophic gastritis, gastric intestinal metaplasia), and early gastric cancer.
- Discussion of non-image-based AI tools like Raman spectroscopy.
Main Results:
- AI systems demonstrate potential in identifying subtle lesions, assessing tumor margins, and reducing interobserver variability.
- AI provides real-time decision support, minimizing biopsies and improving patient outcomes.
- AI aids in detecting precancerous conditions and guiding therapy for early gastric cancer.
Conclusions:
- AI integration in endoscopy faces challenges including validation, user-centric design, and training.
- Balancing AI with clinical expertise is crucial to avoid overreliance and deskilling.
- Future AI integration promises comprehensive diagnosis and personalized therapeutic planning in upper GI care.
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