Effective treatment decisions for colorectal cancer (CRC) depend on the histological classification and microsatellite instability (MSI) status of the patient’s biopsy. In recent years, artificial intelligence (AI) has emerged as a valuable tool in the diagnostic process, offering efficiency, reducing the need for extensive manpower and maintaining accuracy. This review explores recent advancements in AI technology and its effectiveness in identifying prognostic biomarkers related to CRC and aims to inform clinicians and gastroenterologists about novel patient management strategies. A narrative non-systematic review of existing literature on using AI for detecting deficient mismatch repair (dMMR)/MSI in CRC diagnosis was performed. Searches were conducted in the PubMed database using a combination of keywords such as colorectal cancer diagnosis, artificial intelligence and deep learning, focusing on publications from 2019 onward. The reviewed articles exhibited varying outcomes, with each utilizing the CNN model under differing conditions like cohort types and sizes and convolution or filter numbers, highlighting specific strengths and limitations for each model. AI-driven predictive analytics offered researchers superior insights into genomics and proteomics data, elevating patient characterization precision and streamlining pathology workflows.
Jawaher Alsughayyir (2025) studied this question.