Surgical artificial intelligence (AI) has the potential to improve patient safety and clinical outcomes. To date, training such AI models to identify tissue anatomy requires annotations by expensive and rate-limiting surgical domain experts. Herein, we demonstrate and validate a methodology to obtain high quality surgical tissue annotations through crowdsourcing of non-experts, and real-time deployment of multimodal surgical anatomy AI model in colorectal surgery.
CITATION STYLE
Skinner, G., Chen, T., Jentis, G., Liu, Y., McCulloh, C., Harzman, A., … Kim, P. (2024). Real-time near infrared artificial intelligence using scalable non-expert crowdsourcing in colorectal surgery. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01095-8
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