The project, supported by a $1.2 million four-year grant from the National Science Foundation’s Smart and Connected Health program, will use artificial intelligence and machine learning to develop personalized reproductive and fertility predictions, as well as personalized treatments for fertility issues.
The team brings together experts from various fields, including electrical and computer engineering, public health, and medicine. Boston University College of Engineering Professor Ioannis Paschalidis is the principal investigator (PI) of the project. Mahalingaiah, assistant professor of environmental reproductive and women’s health at Harvard Chan School, is co-PI.
“Collaboration for improving discovery and improving care for women across the lifecourse is critically important,” Mahalingaiah said in an October 28, 2019 Boston University Center for Information & Systems Engineering article. “Merged datasets including self reporting, lifestyle, and exposures, clinical-grade data, and data collected from wearable devices will provide personalized insights so that women can be empowered to understand information on the health of their bodies and make the best choices for their health and futures.”
Read the Boston University Center for Information & Systems Engineering article: BU-Harvard Team Wins $1.2M NSF Grant to Improve Women’s Reproductive Health using AI and Machine Learning