Deep Learning Analysis of Cerebral Blood Flow to Identify Cognitive Impairment and Frailty in Persons Living With HIV.

Journal: Journal of acquired immune deficiency syndromes (1999)
PMID: 31714429

Abstract

BACKGROUND: Deep learning algorithms of cerebral blood flow were used to classify cognitive impairment and frailty in people living with HIV (PLWH). Feature extraction techniques identified brain regions that were the strongest predictors.

Authors

  • Patrick Luckett
    Department of Neurology, Washington University School of Medicine, St. Louis, MI.
  • Robert H Paul
    Department of Psychological Sciences, University of Missouri Saint Louis, St. Louis, MI.
  • Jaimie Navid
    Department of Neurology, Washington University School of Medicine, St. Louis, MI.
  • Sarah A Cooley
    Department of Neurology, Washington University School of Medicine, St. Louis, MI.
  • Julie K Wisch
    Department of Neurology, Washington University School of Medicine, St. Louis, MI.
  • Anna H Boerwinkle
    Department of Neurology, Washington University School of Medicine, St. Louis, MI.
  • Dimitre Tomov
    Department of Neurology, Washington University School of Medicine, St. Louis, MI.
  • Beau M Ances
    Department of Radiology, Washington University in St. Louis, School of Medicine, 510 S. Kingshighway, MC 8131, Saint Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, School of Medicine, 510 S. Kingshighway, MC 8131, Saint Louis, MO 63110, USA; Department of Neurology, Washington University in St. Louis, School of Medicine, 510 S. Kingshighway, MC 8131, Saint Louis, MO 63110, USA.

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