Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Machine Learning Approaches to Understand Cognitive Phenotypes in People With HIV.

The Journal of infectious diseases - 17 Mar 2023

Mukerji Shibani S, Petersen Kalen J, Pohl Kilian M, Dastgheyb Raha M, Fox Howard S, Bilder Robert M, Brouillette Marie-Josée, Gross Alden L, Scott-Sheldon Lori A J, Paul Robert H, Gabuzda Dana

Abstract excerpt

Cognitive disorders are prevalent in people with HIV (PWH) despite antiretroviral therapy. Given the heterogeneity of cognitive disorders in PWH in the current era and evidence that these disorders have different etiologies and risk factors, scientific rationale is growing for using data-driven models to identify biologically defined subtypes (biotypes) of these disorders. Here, we discuss the state of science...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cognition
Share to Cognition Disorders

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Cognitive Dysfunction

Share to HIV Infections

Share to Machine Learning

Share to Phenotype

Source

Open in PubMed Open full text

Identifiers

PMID: 36930638
DOI: 10.1093/infdis/jiac293
PMCID: PMC10022709

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Machine Learning Approaches to Understand Cognitive Phenotypes in People With HIV.PMID 36930638Read ↗

Cognitive Phenotypes of HIV Defined Using a Novel Data-driven Approach.Semantic proximity Read ↗

Predicting Neurobehavioral Outcomes in People with HIVSemantic proximity Read ↗

Genome-wide association study of HIV-associated neurocognitive disorder (HAND): A CHARTER group study.Semantic proximity Read ↗

Genome-wide association study of neurocognitive impairment and dementia in HIV-infected adults.Semantic proximity Read ↗

Association of apolipoprotein E epsilon 4 and cognitive impairment in adults living with human immunodeficiency virus: a meta-analysis.Semantic proximity Read ↗

Genomic Factors and Therapeutic Approaches in HIV-Associated Neurocognitive Disorders: A Comprehensive ReviewSemantic proximity Read ↗

The Genetic Fingerprint of HIV in the Brain: Insights into Neurocognitive DysfunctionSemantic proximity Read ↗

Genetic Variations in EIF2AK3 are Associated with Neurocognitive Impairment in People Living with HIV.Semantic proximity Read ↗

CSF proteomic fingerprints for HIV-associated cognitive impairmentSemantic proximity Read ↗

European cross-cultural neuropsychological test battery (CNTB) for the assessment of cognitive impairment in multiple sclerosis: Cognitive phenotyping and classification supported by machine learning techniques.Semantic proximity Read ↗

The Use of Machine Learning Methods in Neurodegenerative Disease Research: A Scoping ReviewSemantic proximity Read ↗

Changing clinical phenotypes of HIV-associated neurocognitive disorders.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.