Student-developed machine-learning techniques make surgeries safer, easier to review
An interdisciplinary fellowship with the Data Science Institute has resulted in a promising machine-learning technology that can effectively track complex surgical activity, thus having the potential to improve patient outcomes, safety and documentation.
