November 13, 2024
AIM-AHEAD Traineeship in Advanced Data Analysis using the Bridge2AI AI/ML for Clinical Care Network
The AIM-AHEAD Bridge2AI for Clinical Care Training Program is intended to increase researcher diversity in AI/ML by leveraging Bridge2AI AI/ML for Clinical Care Network data and tools.
October 21, 2024
Congratulations to Dr. Christopher G Chute, MD, DrPH, on his election to the National Academy of Medicine.Dr. Chute is joined by 99 other new members of the Academy, recognized for their professional achievement and commitment to service in the fields of health and medicine.
May 29, 2024
The Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) program seeks to increase the participation and engagement of the researchers and communities currently underrepresented in AI/ML modeling and applications through mutually beneficial partnerships.
April 4, 2023
The NIH Common Fund issued two new notice of funding opportunity announcements from the Common Fund Data Ecosystem (CFDE): OTA-23-004 and RFA-RM-23-002. The purpose of these funding announcements is to establish the CFDE Data Resource Center, Knowledge Center, and Integration and Coordination Center.
April 01, 2024
Here & Now’s Scott Tong talks with Dr. Yael Bensoussan. She is one of the leaders of a study on Voice AI called Bridge2AI funded by the National Institutes of Health. She also directs the Health Voice Center at the University of South Florida.
February 23, 2024
With deep learning methods revolutionizing life sciences, researchers bet on de novo proteins and cell mapping models to deliver customized precision medicines.
September 13, 2022
The National Institutes of Health will invest $130 million over four years, pending the availability of funds, to accelerate the widespread use of artificial intelligence (AI) by the biomedical and behavioral research communities.
September 15, 2021
The U.S. Department of Energy (DOE) announced $1 million for a one-year collaborative research project to develop artificial intelligence (AI) and machine learning (ML) algorithms for biomedical, personal healthcare, or other privacy-sensitive datasets.