Washington University School of Medicine is joining the National Institutes of Health (NIH)’s Bridge2AI program, an estimated $130 million initiative. One project aims to develop a framework for using artificial intelligence to diagnose disease based on the sound of patients’ voices.
A center in the Institute of Clinical and Translational Sciences received a grant establishing the School of Medicine as a coordinating center for the Short-Term Research Experience Program to Unlock Potential. STEP-UP is a National Institutes of Health (NIH) program to introduce scholars underrepresented in medicine to medical research.
Using Fitbits and a novel machine learning model, a multi-institutional team led by Washington University’s Chenyang Lu is ushering in the next step in personalization for treatment of depression.
Ari Stern, associate professor of mathematics and statistics in Arts & Sciences, won a $237,648 grant from the National Science Foundation for a project titled “Structure-Preserving Hybrid Finite Element Methods.”
Fred Ssewamala, the William E. Gordon Distinguished Professor at the Brown School, received a five-year $3.2 million grant from the National Institutes of Health to lead a study on intervention strategies for HIV treatments among Ugandan youth. The study could advance intervention science for HIV care globally.
New research led by Kiersten Ruff, a senior research scientist in the lab of Rohit Pappu at the McKelvey School of Engineering, has uncovered the rules that govern how unfolded proteins are identified — and found that exceptions to the rules may play a role in dysfunctional cells.
Research from Ryan Bogdan’s BRAIN Lab in Arts & Sciences finds signs of psychopathology persist into mid-adolescence in kids exposed to cannabis in the womb.
To develop guidelines to evaluate artificial intelligence (AI) in nuclear-medicine imaging, an interdisciplinary team established by Richard L. Wahl, MD, director of Mallinckrodt Institute of Radiology (MIR) and led by Abhinav Jha, assistant professor at the McKelvey School of Engineering, published Recommendations for Evaluation of AI for Nuclear Medicine in the Journal of Nuclear Medicine.
