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

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.