This $244,306 project grant from the National Science Foundation's Computer and Information Science and Engineering program will fund the development of an artificial intelligence-enabled coaching system to enhance surgical teamwork in cardiac operating rooms. Led by researchers at Brigham and Women's Hospital in Houston, Texas, the grant aims to design multimodal sensing hardware, data-driven algorithms, and an interface to monitor, assess, and improve collaboration among healthcare...
This $349,683 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund the development of an AI coaching system to enhance surgical teamwork in cardiac operating rooms. Led by William Marsh Rice University, the grant supports the design of multimodal sensing hardware, data-driven algorithms, and an interface to model and computationally generate interpretable feedback and interventions improving teamwork. Researchers will develop a...
This $659,809 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will develop a novel system to identify cognitive and affective states, behavioral patterns, and contextual factors contributing to medical errors. The research team at Virginia Polytechnic Institute & State University (Virginia Tech) will implement multi-modal machine-learning algorithms using data from wearable sensors, audio, video, and...
This National Science Foundation (NSF) Project Grant awarded under the Computer and Information Science and Engineering (CFDA 47.070) program provides $1,200,000 to the Regents of the University of Michigan to develop multimodal techniques to enhance intra- and post-operative learning and coordination between attending and resident surgeons. The key objectives are to: Collect and curate a dataset of up to 100 laparoscopic cholecystectomy surgeries, including surgeons' gaze, operating room...
This Project Grant award from the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under the Discovery and Applied Research for Technological Innovations to Improve Human Health program (CFDA 93.286) provides $709,358 to develop an artificial intelligence (AI) surgical coaching system to enhance performance and outcomes in urologic endoscopy procedures. The project aims to create predictive machine learning models by analyzing video data and neuroergonomic metrics captured...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award of $519,645 to the University of Toledo Health Science Campus Division will develop a novel system to identify cognitive and affective states, behavioral patterns, and contextual factors contributing to medical errors. The project, titled "Collaborative Research: SCH: Clinical Adaptive Performance Enhancement through Human-AI Teaming (CAPE-HAT)," aims...
This Project Grant award from the National Science Foundation's (NSF) Engineering Program (CFDA 47.041) supports a collaborative research project led by Emory University to develop an interactive artificial intelligence (AI) teammate system for upskilling mental health workers. The $548,297 award aims to understand how AI can be effectively and ethically integrated into mental health work to address the shortage of skilled workers and improve access to research-supported treatment protocols. The...
This is a $300,000 EAGER (Early-Concept Grants for Exploratory Research) project grant awarded by the National Science Foundation's Engineering program (CFDA 47.041) to design neuro-adaptive technology for robotic-assisted surgery. The grant supports research to monitor surgeons' workload levels, understand the causes of mental overload, and develop interventions using an AI-powered multi-sensing system and context-awareness architecture. The goal is to refine remote surgery techniques to make...
The National Science Foundation Division of Information and Intelligent Systems awarded a $600,000 Project Grant to the Massachusetts Institute of Technology from September 1, 2022 to August 31, 2026 under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support the development of machine learning-driven user interfaces and contextual displays to help clinicians synthesize information from patient medical records. Researchers will create a novel...
The National Science Foundation (NSF) awarded a $1,199,083 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Carnegie Mellon University (CMU) to develop an AI-driven intervention system that uses multimodal sensing from a smartwatch to guide post-operative patients through recovery procedures. The system aims to help patients manage their recovery, including maintaining appropriate activity levels, pain management, and wound care, through...