Real-time near infrared artificial intelligence using scalable non-expert crowdsourcing in colorectal surgery.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 38649447.
- Also identified by DOI 10.1038/s41746-024-01095-8 and PMC identifier 11035672.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
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.