Analyzing Surgical Technique in Diverse Open Surgical Videos With Multitask Machine Learning.

Objective: To overcome limitations of open surgery artificial intelligence (AI) models by curating the largest collection of annotated videos and to leverage this AI-ready data set to develop a generalizable multitask AI model capable of real-time understanding of clinically significant surgical behaviors in prospectively collected real-world surgical videos.

Design, Setting, And Participants: The study team programmatically queried open surgery procedures on YouTube and manually annotated selected videos to create the AI-ready data set used to train a multitask AI model for 2 proof-of-concept studies, one generating surgical signatures that define the patterns of a given procedure and the other identifying kinematics of hand motion that correlate with surgeon skill level and experience. The Annotated Videos of Open Surgery (AVOS) data set includes 1997 videos from 23 open-surgical procedure types uploaded to YouTube from 50 countries over the last 15 years.

On-demand electrically controlled drug release from resorbable nanocomposite films.

Electroresponsive materials are promising carriers for developing drug delivery systems (DDSs) with excellent spatial, temporal, and dosage control over drug release. Current electroresponsive systems use high voltages (2-25 V), are not bioresorbable, or use materials with unknown long-term biocompatibility. We report here a nanocomposite film that is resorbable, electroresponsive at low voltages (<-2 V), and composed of entirely FDA-approved materials.