Scientists using math, artificial intelligence to study concussions

A new technique utilizing computational techniques to sift through large amounts of data is helping scientists to streamline a process that could help diagnose and treat traumatic brain injury patients quicker and more thoroughly. A press release about the study was issued last Wednesday. For the study, data was collected from 586 patients with acute […]

A new technique utilizing computational techniques to sift through large amounts of data is helping scientists to streamline a process that could help diagnose and treat traumatic brain injury patients quicker and more thoroughly.

A press release about the study was issued last Wednesday.

For the study, data was collected from 586 patients with acute traumatic brain injury from trauma centers. The results revealed that concussion, or mild traumatic brain injury, could be stratified into multiple subgroups with diverse prognoses.

Among them was a large group of patients who, despite normal brain scans, demonstrated poor recovery and a tendency to get worse, three-to-six months after the injury. These patients were likely to suffer from post-traumatic stress disorder.

“Scientists have used a unique computational technique that sifts through big data to identify a subset of concussion patients with normal brain scans, who may deteriorate months after diagnosis and develop confusion, personality changes and differences in vision and hearing, as well as post-traumatic stress disorder,” the press release reads.

The computer is able to identify a particular set of molecular biomarkers that could pave the way to precision medicine for TBI patients.

“ Investigators headed by scientists at UC San Francisco and its partner institution Zuckerberg San Francisco General Hospital and Trauma Center (ZSFG) analyzed an unprecedented array of data, using a machine learning tool called topological data analysis (TDA), which ‘visualizes’ diverse datasets across multiple scales, a technique that has never before been used to study traumatic brain injury.”

TDA actually uses math derived from topology to create a summary or compressed representation of all the data points using algorithms that map patient data.

Traumatic brain injury results in approximately 52,000 deaths, 257,000 hospitalizations and 2.2 million emergency department visits in the United States annually, according to the Centers for Disease Control and Prevention’s Injury Center.

These injuries can lead to widespread lesions throughout the brain’s white matter, as well as a “cascade of secondary injury mechanisms that evolve over times.” The heterogeneity of the manifestations of these secondary injuries is one significant obstacle that thwarts the development of new treatments, the authors note in their paper.