Machine Learning Helps Improve Brain Injury Outcomes

Machine learning model may foster life-saving care for patients with traumatic brain injury as per a study at the University of Pittsburgh School of Medicine, published in the journal Radiology. Traumatic brain injury (TBI) — the leading cause of death in people under the age of 45 — is one of the devastating public health issues in the U.S. that affects nearly 3 million people every year across the nation.

Generally, the TBI patients take two weeks to begin their recoveries from the coma. The advanced machine-learning algorithm helps analyze brain scans of TBI patients quickly and accurately to deliver the best care at the right time.

Advanced Artificial Intelligence Model For TBI Recovery

The prognostic model helps predict the survival and recovery of TBI patients even six months after the injury.

“There is a great need for better quantitative tools to help intensive care neurologists and neurosurgeons make more informed decisions for patients in critical condition. This collaboration with Dr. Okonkwo’s (co-senior author and professor of neurological surgery at Pitt and UPMC) team gave us an opportunity to use our expertise in machine learning and medical imaging to develop models that use both brain imaging and other clinically available data to address an unmet need,” says corresponding author Shandong Wu, PhD, associate professor of radiology, bioengineering and biomedical informatics at Pitt.

The advanced artificial intelligence research thereby helps to improve emergency decision making among clinicians to aid better outcomes for TBI patients.

Source-Medindia