Ensemble machine learning classification of daily living abilities among older people with HIV.

ABSTRACT:

Background

clinically relevant methods to identify individuals at risk for impaired daily living abilities secondary to neurocognitive impairment (ADLs) remain elusive. This is especially true for complex clinical conditions such as HIV-Associated Neurocognitive Disorders (HAND). The aim of this study was to identify novel and modifiable factors that have potential to improve diagnostic accuracy of ADL risk, with the long-term goal of guiding future interventions to minimize ADL disruption.

Methods

study participants included 79 people with HIV (PWH; mean age = 63; range = 55-80) enrolled in neuroHIV studies at University California San Francisco (UCSF) between 2016 and 2019. All participants were virally suppressed and exhibited objective evidence of neurocognitive impairme

SUBMITTER: Paul R 

PROVIDER: S-EPMC8129893 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature