MTP4.10 Med-Gemini and Colorectal Surgery; Are we ready?

Résumé fourni par la source

Abstract Aims This review evaluates the potential of Med-Gemini, an advanced AI model developed by Research and DeepMind, for integration into surgery. It aims to explore its multimodal capabilities in reasoning, data analysis (text, images, patient records), and complex scenario-solving, particularly in enhancing diagnostic accuracy, surgical planning, and patient outcomes, while addressing challenges in resource-limited settings. Methods The analysis synthesizes existing literature on AI applications in surgery, including intraoperative guidance, image segmentation, complication prediction, automated histology evaluation, and patient-reported outcome assessment. Med-Gemini’s technical advancements are contextualized against these use cases. Results Current AI applications in surgery demonstrate benefits in decision-making automation, complication prediction, and workflow efficiency. Med-Gemini’s advanced reasoning and multimodal data processing capabilities suggest potential for optimizing surgical planning, improving diagnostic precision, and mitigating resource disparities in low-income settings by reducing reliance on costly equipment. Conclusion While Med-Gemini’s direct application in surgery remains limited, its technical features align with emerging AI trends in healthcare. Future integration could enhance surgical outcomes and accessibility, particularly in resource-constrained environments. However, implementation requires rigorous validation, structured oversight, and safeguards to prevent clinical over-reliance. Collaborative efforts between developers and clinicians are essential to ensure ethical, safe, and effective adoption, aligning with the evolving role of AI in modern medicine.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.