Personalized Colorectal Cancer Screening Using Artificial Intelligence to Improve Early Detection and Prevention A Study Comparing AI-assisted and Traditional Colonoscopy in Adults Aged 50 to 69

What this Trial Is About

Researchers are evaluating new personalized colorectal cancer CRC screening methods using artificial intelligence AI to improve early detection. Colorectal cancer is a common and deadly disease, with risk factors including age, obesity, smoking, diet, and physical activity. This study aims to develop a predictive risk model to tailor screening strategies, moving from a one-size-fits-all approach to personalized prevention by integrating AI and patient risk profiles. Participants will undergo colonoscopy either with traditional methods or with AI assistance using the GI Genius device to help detect colorectal lesions. Those testing positive for fecal occult blood through a regional screening program will be randomized to receive either standard colonoscopy or AI-assisted colonoscopy. Data on diet, physical activity, and other risk factors will also be collected through questionnaires. Follow-up colonoscopies may be scheduled based on findings at 1, 3, or 5 years. Participants will be involved in interviews, receive preparation instructions, complete questionnaires, and undergo colonoscopy according to their assigned group. The study will monitor adenoma detection rates and other outcomes over 18 months, with a total study duration of 72 months. Researchers will analyze data to improve screening precision and reduce unnecessary invasive procedures, aiming to optimize screening pathways based on individual risk.

Artificial Intelligence-based Screening Models for Prevention and Early Detection of Colorectal Cancer