Artificial intelligence and automation in endoscopy and surgery

Area of Science:

• Medical Technology
• Artificial Intelligence
• Gastroenterology & Surgery

Background:

• Modern endoscopy utilizes digital technology for high-resolution imaging and robotic articulation.
• Digitization enables comprehensive video data capture of internal anatomy during procedures.
• Endoscopic video data contain rich information on patient anatomy and surgical events.

Purpose of the Study:

• To summarize state-of-the-art artificial intelligence for computer-assisted interventions in gastroenterology and surgery.
• To highlight the potential of AI in leveraging endoscopic video data for enhanced medical procedures.

Main Methods:

• Review of current artificial intelligence applications, particularly supervised deep learning, in endoscopy.
• Analysis of how endoscopic video data can be integrated with other patient records.
• Focus on AI's role in navigation, image interpretation, and robotic manipulation.

Main Results:

• AI, especially deep learning, can utilize endoscopic video data for procedural assistance.
• Computer-assisted interventions can improve navigation, automate image interpretation, and aid robotic manipulation.
• Integration of video data with patient records offers comprehensive insights.

Conclusions:

• AI holds significant promise for advancing computer-assisted interventions in gastroenterology and surgery.
• AI-driven endoscopy can lead to more effective diagnostic and therapeutic procedures.
• The integration of AI is crucial for the future of interventional endoscopy.