VA, ORNL and Harvard develop novel method to identify complex medical relationships

A team of researchers from the Department of Veterans Affairs, Oak Ridge National Laboratory, Harvard’s T.H. Chan School of Public Health, Harvard Medical School and Brigham and Women’s Hospital has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

PSC and Partners to Lead $7.5-Million Project to Allocate Access on NSF Supercomputers

The NSF has awarded $7.5 million over five years to the RAMPS project, a next-generation system for awarding computing time in the NSF’s network of supercomputers. RAMPS is led by the Pittsburgh Supercomputing Center and involves partner institutions in Colorado and Illinois.

St. Louis Comes Together to Announce the Taylor Geospatial Institute

The Taylor Geospatial Institute is a first-of-its-kind institution that brings together eight leading research institutions to collaborate on research into geospatial technology.

Big Data Analytics Enables Scientists to Model COVID-19 Spread

Researchers will use big data analytics techniques to develop computational models to predict the spread of COVID-19. They will utilize forward simulation from a given patient and the propagation of the infection into the community; and backward simulation tracing a number of verified infections to a possible patient “zero.” The project also will provide quick and automatic contact tracing and leverages the researchers’ prior experience in modeling Ebola spread.

Staying Two Steps Ahead of the Coronavirus

A method of predicting the coronavirus spread – pioneered and developed by Weizmann Institute scientists – may enable authorities to focus efforts on areas where an outbreak is anticipated and relieve measures taken in others. Several countries, including the U.S., are adopting the new method

Weizmann Scientists Devise New Algorithm that Predicts Gestational Diabetes

Using machine learning to analyze data on nearly 600,000 pregnancies, researchers devised an algorithm that identified nine parameters – out of more than 2,000 analyzed – that can predict which women are at risk of gestational diabetes. The parameters can identify risk early in – even before – pregnancy, enabling early intervention.

FAU Schmidt College of Medicine Launches Genomics and Predictive Health Certificate

The lack of understanding of health providers and patients is a major barrier to the integration of genomics into personalized medicine. This innovative certificate program will provide health professionals and scientists with the requisite skills they need to interpret and incorporate this new knowledge into a patient care model that emphasizes individually tailored prevention, diagnosis and treatment.