I-Corps: Centralized, Cloud-Based, Artificial Intelligence (AI) Video Analysis for Enhanced Intubation Documentation and Continuous Quality Control

The broader impact/commercial potential of this I-Corps project is the development of an artificial intelligence (AI)-powered platform for medical video analysis. Currently, medical professionals often face the challenge of timely patient care reporting. This technology is designed to enable them to upload procedure videos and receive immediate, essential documentation. The initial focus of the project is on airway management including critical procedures such as emergency intubation. In addition, the technology may optimize workflow by accelerating the completion of essential documentation and quality assurance tasks, effectively reducing providers’ burdens. This efficiency may translate to more time for direct patient care, improved patient outcomes, and an elevated standard of emergency medical services. This I-Corps project is based on developing an artificial intelligence (AI)-based, deep learning neural network to analyze medical videos and accurately output events in medical procedures. The technology represents the culmination of extensive research in airway management techniques and the application of AI in clinical settings, with a particular focus on video laryngoscopy. Intubation videos from modern video laryngoscopes were used to annotate airway anatomy in every frame, culminating in a comprehensive dataset. This dataset informs the neural network training and validation. The technology is designed to provide an AI solution that assists in interpreting and understanding complex medical procedures both quickly and accurately. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.