Skip to content
Automated Brain Scans, Machine Learning Soon to Inform Outcomes in Severe TBI
May 25, 2022
Austin, TX (Law Firm Newswire) May 25, 2022 – Sustaining a traumatic brain injury (TBI) is not only frightening but can be extremely serious. The severity of the trauma often dictates the long-term prognosis. However, no matter how much experience a doctor has, there is always an element of uncertainty in not only the diagnosis but the eventual recovery of the patient.
TBI is a serious public health issue, and each year in the U.S., close to 3 million people seek care for TBI, with many more never seeking care. Traumatic brain injury remains a leading cause of death in individuals under the age of 45.
Unfortunately, there is often some uncertainty about a TBI diagnoses about whether there was an injury or about the severity of the injury. That uncertainty may be about to become moot thanks to a prognostic model developed by UPMC neurotrauma surgeons and the University of Pittsburgh School of Medicine data scientists. The advanced machine-learning algorithm they partnered to create can quickly analyze brain scans and related clinical data. This in turn allows for a quick and accurate prediction of recovery and survival rate at the six-month mark after the initial injury.
This is a ground-breaking development can make a big difference in identifying those most likely to recover. The new algorithm has the potential to screen patients shortly after they are admitted to a hospital, can help physicians make a diagnosis, and can improve a physician’s ability to provide the best care at the appropriate time. This tool may be even more powerful as it delivers a snapshot of each patient. No two brain injuries and outcomes are alike. Knowing what each patient is facing, in advance of full out treatment, has the potential to save more lives and provide better-personalized care.
The custom artificial intelligence (AI) model can process multiple brain scans for each patient and combine it with an estimate of coma severity, information on a patient’s vitals, heart function, and blood work. Additionally, this particular model is trained on different image-taking protocols.
“This is good news,” indicated Austin traumatic brain injury lawyer, Brooks Schuelke. “Any tool that assists physicians to diagnose a TBI faster, better, and with more accuracy is bound to be a winner.”
Learn more at http://www.civtrial.com
Schuelke Law PLLC
3011 N. Lamar Blvd
Ste. 200
Austin, TX 78705
Call (512) 476-4944
The post Automated Brain Scans, Machine Learning Soon to Inform Outcomes in Severe TBI first appeared on Law Firm Newswire.
