Data-driven distillation and precision prognosis in traumatic brain injury with interpretable machine learning.

Dec 04, 2023

Experts: Andrew Tritt,John K Yue,Adam R Ferguson,Abel Torres Espin,Lindsay D Nelson,Esther L Yuh,Amy J Markowitz,Geoffrey T Manley,Kristofer E Bouchard,

Traumatic brain injury (TBI) affects how the brain functions in the short and long term. Resulting patient outcomes across physical, cognitive, and psychological domains are complex and often difficult to predict. Major challenges to developing personalized treatment for TBI include distilling large quantities of complex data and increasing the precision with which patient outcome prediction (prognoses) can be rendered. We developed and applied interpretable machine learning methods to TBI patient data. We show that complex data describing TBI patients’ intake characteristics and outcome phenotypes can be distilled to smaller sets of clinically interpretable latent factors. We demonstrate that 19 clusters of TBI outcomes can be predicted from intake data, a ~ 6× improvement in precision over clinical standards. Finally, we show that 36% of the outcome variance across patients can be predicted. These results demonstrate the importance of interpretable machine learning applied to deeply characterized patients for data-driven distillation and precision prognosis.
© 2023. The Author(s).

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ABOUT THE EXPERTS

Andrew Tritt,John K Yue,Adam R Ferguson,Abel Torres Espin,Lindsay D Nelson,Esther L Yuh,Amy J Markowitz,Geoffrey T Manley,Kristofer E Bouchard,

Andrew Tritt

Applied Math and Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.

John K Yue

Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA.

Department of Neurosurgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.

Adam R Ferguson

Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA.

Department of Neurosurgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.

San Francisco Veterans Affairs Healthcare System, San Francisco, CA, USA.

Abel Torres Espin

Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA.

Department of Neurosurgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.

Lindsay D Nelson

Departments of Neurosurgery and Neurology, Medical College of Wisconsin, Milwaukee, WI, USA.

Esther L Yuh

Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA.

Department of Neurosurgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.

Amy J Markowitz

Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA.

Department of Neurosurgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.

Geoffrey T Manley

Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA.

Department of Neurosurgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.

Weill Neurohub, University of California San Francisco, San Francisco, CA, USA.

Weill Neurohub, University of California Berkeley, Berkeley, CA, USA.

Kristofer E Bouchard

Weill Neurohub, University of California Berkeley, Berkeley, CA, USA. kebouchard@lbl.gov.

Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. kebouchard@lbl.gov.

Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. kebouchard@lbl.gov.

Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience, University of California Berkeley, Berkeley, CA, USA. kebouchard@lbl.gov.