Machine Learning Approaches to Understand Cognitive Phenotypes in People With HIV is a research paper published in The Journal of Infectious Diseases (2023). On theSindex it has a DataRank of 0.520. It has been cited 31 times.
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0.520
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0
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Tracking HIV Infection and Alcohol Abuse CNS Comorbidity with Neuroimaging
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The Johns Hopkins Center for AIDS Research (JHU CFAR)
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Impact of Treatment on Brain Integrity in the Earliest Stages of HIV Infection
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CNS Viral Escape in HIV-infected Adults
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Genetic, Imaging, and Cognition study of Positive Valence Systems in Psychotic Syndromes
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Chronic HIV Infection and Aging in NeuroAIDS (CHAIN) Center
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Brain aging and cognitive impairment in persons with HIV
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NNTC Data Coordinating Center
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Neuroimmune mechanisms of depression in adults with HIV infection
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Immune Activation, Cerebral Metabolic Activity and Depression in Treated HIV-Infection
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Functional Imaging Reserve in NeuroHIV (FIRN)
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Machine learning to distinguish HAND from Alzheimer's disease in HIV over age 60
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Secondary Analysis of Cognitive Data from the Multi-Center AIDS Cohort Study (MACS) to Identify Longitudinal Change Phenotypes in HIV+ Individuals
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Keywords
Additional file 1 of Translocation of bacterial LPS is associated with self-reported cognitive abilities in men living with HIV receiving antiretroviral therapy
Additional file 1 of Translocation of bacterial LPS is associated with self-reported cognitive abilities in men living with HIV receiving antiretroviral therapy