AIMC Topic: Endoscopy, Gastrointestinal

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Development of artificial intelligence system for quality control of photo documentation in esophagogastroduodenoscopy.

Surgical endoscopy
BACKGROUND: Esophagogastroduodenoscopy (EGD) is generally a safe procedure, but adverse events often occur. This highlights the necessity of the quality control of EGD. Complete visualization and photo documentation of upper gastrointestinal (UGI) tr...

Striving for quality improvement: can artificial intelligence help?

Best practice & research. Clinical gastroenterology
Artificial intelligence (AI) is of keen interest for global health development as potential support for current human shortcomings. Gastrointestinal (GI) endoscopy is an excellent substrate for AI, since it holds the genuine potential to improve qual...

Artificial intelligence and its impact on quality improvement in upper and lower gastrointestinal endoscopy.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Artificial intelligence (AI) and its application in medicine has grown large interest. Within gastrointestinal (GI) endoscopy, the field of colonoscopy and polyp detection is the most investigated, however, upper GI follows the lead. Since endoscopy ...

Artificial intelligence: Thinking outside the box.

Best practice & research. Clinical gastroenterology
Artificial intelligence (AI) for luminal gastrointestinal endoscopy is rapidly evolving. To date, most applications have focused on colon polyp detection and characterization. However, the potential of AI to revolutionize our current practice in endo...

Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning-Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: The early diagnosis of various gastrointestinal diseases can lead to effective treatment and reduce the risk of many life-threatening conditions. Unfortunately, various small gastrointestinal lesions are undetectable during early-stage ex...

Detection of multiple lesions of gastrointestinal tract for endoscopy using artificial intelligence model: a pilot study.

Surgical endoscopy
BACKGROUND: This study was aimed to develop a computer-aided diagnosis (CAD) system with deep-learning technique and to validate its efficiency on detecting the four categories of lesions such as polyps, advanced cancer, erosion/ulcer and varices at ...

HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy.

Scientific data
Artificial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of medical personnel for the cumbersome and tedious process to manually label training data. The...