Development of prediction models for liver metastasis in colorectal cancer based on machine learning: a population-level study.

Background: Liver metastasis (LM) is of vital importance in making treatment-related decisions in patients with colorectal cancer (CRC). The aim of our study was to develop and validate prediction models for LM in CRC by making use of machine learning.

Methods: We selected patients diagnosed with CRC from 2010 to 2015 from the Surveillance, Epidemiology, and End Results (SEER) database.

Artificial intelligence algorithms for real-time detection of colorectal polyps during colonoscopy: a review.

Colorectal cancer (CRC) is one of the most common cancers worldwide. Early detection and removal of colorectal polyps during colonoscopy are crucial for preventing such cancers. With the development of artificial intelligence (AI) technology, it has become possible to detect and localize colorectal polyps in real time during colonoscopy using computer-aided diagnosis (CAD).