The development of deep learning systems in artificial intelligence (AI) has enabled advances in endoscopy, and AI-aided colonoscopy has recently been ushered into clinical practice as a clinical decision-support tool. This has enabled real-time AI-aided detection of polyps with a higher sensitivity than the average endoscopist, and evidence to support its use has been promising thus far. This review article provides a summary of currently published data relating to AI-aided colonoscopy, discusses current clinical applications, and introduces ongoing research directions. We also explore endoscopists’ perceptions and attitudes toward the use of this technology, and discuss factors influencing its uptake in clinical practice.

Sarcopenia, which is characterized by progressive and generalized loss of skeletal muscle mass and strength, has been well described to be associated with numerous poor postoperative outcomes, such as increased perioperative mortality, postoperative sepsis, prolonged length of stay, increased cost of care, decreased functional outcome, and poorer oncological outcomes in cancer surgery. Multimodal prehabilitation, as a concept that involves boosting and optimizing the preoperative condition of a patient prior to the upcoming stressors of a surgical procedure, has the purported benefits of reversing the effects of sarcopenia, shortening hospitalization, improving the rate of return to bowel activity, reducing the costs of hospitalization, and improving quality of life. This review aims to present the current literature surrounding the concept of sarcopenia, its implications pertaining to colorectal cancer and surgery, a summary of studied multimodal prehabilitation interventions, and potential future advances in the management of sarcopenia.