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 $249,250 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. Over four years, researchers at the Massachusetts Institute of Technology will design multimodal hardware and algorithms to model, monitor, and generate interpretable feedback on teamwork dynamics using data from cardiac procedures. The goal is to mitigate human...
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 federal 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 and validate an artificial intelligence (AI) surgical coaching system to enhance surgical performance and patient outcomes during urologic endoscopy procedures. The project aims to create AI and machine learning models that can...
This federal Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 - Cardiovascular Diseases Research) in the amount of $2,015,958 supports research to develop a multidomain cardiothoracic surgeon operative performance index and identify associated biomarkers. The project, led by the Regents of the University of Michigan, will leverage expertise in applying data analytics to real operative video and a partnership with the U.S. Tennis Association's player development...
This Project Grant from the National Science Foundation's Office of Emerging Frontiers and Multidisciplinary Activities provides $149,913 to Clemson University under the Engineering program (CFDA 47.041) from October 1, 2022 to September 30, 2023. The funding supports a multidisciplinary team at Clemson University to understand attitudes and barriers regarding robotic-assisted surgical devices, integrate expert perspectives on challenges and opportunities for their adoption, validate a...
This $787,050 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), supports the development of autonomous algorithms for rapid, cost-effective annotation of minimally invasive surgical video data. The project aims to address the bottleneck of obtaining large-scale, high-quality datasets for training AI systems to provide valuable...
This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) provides $100,000 to The Research Foundation For The State University Of New York (RF-SUNY) to research and develop a multimodal visualization and progress-tracking system for cardiac rehabilitation. The overarching goal is to understand how cardiac experts view and decide on the progress of patients using multimodal data, and then design a system that can provide...
This $345,207 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop foundational methods for integrating expert clinicians' visual search behaviors, as captured through eye gaze patterns, into machine learning (ML) pipelines for medical image analysis. The project seeks to enhance the predictive performance, interpretability, and clinical trustworthiness of AI-enabled healthcare solutions...
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...