Machine Learning

Vanderbilt researchers used a machine learning algorithm and data from more than 26,000 hospital stays to predict who would and would not be discharged over the next 24 hours. Read More

Vanderbilt researchers have won a National Science Foundation grant to use wearable technologies to detect problem behaviors in children and adolescents with intellectual and developmental disabilities and offer strategies to protect them from potential harm. Children with intellectual and developmental disabilities (IDD) are at increased risk of showing problem behavior that expose them to being... Read More

Vanderbilt researchers have won a National Science Foundation grant to use wearable technologies to detect problem behaviors in children and adolescents with intellectual and developmental disabilities and offer strategies to protect them from potential harm. Children with intellectual and developmental disabilities (IDD) are at increased risk of showing problem behavior that expose them to being... Read More

Professor and entrepreneur finds startup success with Vanderbilt’s spirit of collaboration and innovation. Read More

Multi-university team tackles safety systems for autonomous eVTOLs Vanderbilt engineers are part of a NASA-funded, multi-institution effort to develop safety systems for a mode of transportation that doesn’t exist yet—small, commercial, autonomous planes that move people by air between locations in large, crowded cities. The task is a formidable one with machine learning at its... Read More

Multi-university team tackles safety systems for autonomous eVTOLs Vanderbilt engineers are part of a NASA-funded, multi-institution effort to develop safety systems for a mode of transportation that doesn’t exist yet—small, commercial, autonomous planes that move people by air between locations in large, crowded cities. The task is a formidable one with machine learning at its... Read More

An interdisciplinary fellowship with the Data Science Institute has resulted in a promising machine-learning technology that can effectively track complex surgical activity, thus having the potential to improve patient outcomes, safety and documentation. Read More

Vanderbilt investigators have devised a system to alert health IT teams to deteriorating performance in clinical prediction models. Read More

A trans-institutional team of Vanderbilt engineering, data science and clinical researchers has developed a novel approach for monitoring bone stress in recreational and professional athletes, with the goal of anticipating and preventing injury. Using machine learning and biomechanical modeling techniques, the researchers built multisensory algorithms that combine data from lightweight, low-profile wearable sensors in shoes... Read More

Drug-tolerant persister cells–those that survive cancer treatment–found to rely on similar survival mechanisms across cancers, in a groundbreaking study led by Vanderbilt researchers. Read More

A new, $8.7 million project—Design. R–AI-assisted CPS Design—involves pathbreaking work for the Defense Advanced Research Projects Agency as future cyber-physical systems will rely less on human control and more machine learning algorithms and artificial intelligence processors. Read More

Rebecca Ihrie and Jonathan Irish are leading the development of machine learning applications for brain cancer research. Read More

The goal of the project—Risk-Aware Market Clearing—is a blueprint for an end-to-end, data-driven approach that balances cost and minimizes system-level risk. Market clearing is the process that keeps the supply level to the demand with no leftover of either. Read More

Jonathan Irish joins an international collaboration by deploying artificial intelligence to optimize COVID-19 treatment and vaccine development. Read More

Zhijun Yin, PhD, assistant professor of Biomedical Informatics at Vanderbilt University Medical Center, has received the National Cancer Institute’s Method to Extend Research in Time Award (or MERIT Award) for Early Stage Investigators. Read More

A new tool developed by Vanderbilt engineers, in collaboration with clinical and informatic experts, can unearth novel co-morbidities from routinely collected, anonymized electronic medical records. Read More

In machine learning, generative adversarial networks (GANs) involve two artificial neural networks squaring off, one, the generator, trying to delude the other, the discriminator, into accepting synthetic data as real. Beyond their science and engineering applications, GANs can generate utterly convincing “photographs” of people who do not exist. Unrestricted use on a wide scale of... Read More

Simulated electronic health records could avoid patient privacy risks and help speed discovery. Read More

Machine learning on unlabeled electronic health record data has shed light on the emergence of cardiovascular disease. Read More

Vanderbilt professor Brett Byram plans to use a grant from the National Science Foundation to utilize machine learning for the delivery of better real-time brain images, an advance decades in the making. Read More