With the inter- and multi-disciplinary collaboration of the medical community with technologists in conjunction with a disproportionately alarming doctor-patient ratio, it has now become a matter of concern for researchers to enhance patient care with advanced technology along with the reduction of burden on medical professionals. Artificial Intelligence (AI) has now been accepted willingly in the healthcare sector, which has led to a tremendous increase in computational power and large data handling capabilities and is widely used in gastrointestinal endoscopy. The objective of this review is to explore the state of current literature on different AI-based methods applied in intestinal endoscopy for the detection of colonic polyps. A detailed non-systematic literature review was conducted to identify all relevant studies using PubMed/MEDLINE, Scopus, EMBASE, and Google Scholar databases. The technique of AI systems, model building steps, and diagnostic measuring techniques are also discussed. In the automated diagnosis of polyps, AI-based platforms have achieved clinically acceptable diagnostic efficiency. AI-based methods can be of clinical importance in gastroenterology, and as computing strength and algorithms enhance, the application is likely to grow and expand in the field.
All Science Journal Classification (ASJC) codes
- Chemistry (miscellaneous)
- Materials Science(all)
- Energy Engineering and Power Technology
- Physical and Theoretical Chemistry
- Artificial Intelligence
- Applied Mathematics