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Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations

Cell(2024)10.1016/j.cell.2024.11.012Source: DataRank Database

Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations is a research paper published in Cell (2024). On theSindex it has a DataRank of 0. It has been cited 37 times.

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Open Access37 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (28 grants)Impact (FWCI 19.06)OA: hybridTopics (36)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (15)

Beatrice Borsari ORCID,Yunyang Li,Susanna Liu ORCID,Yuan Gao ORCID,Xin Xin ORCID

Live enrichment

PubMed:39706190 OpenAlex:https://openalex.org/W4405567015

National Institutes of Health

Grant: U01DA041156

National Institutes of Health

Grant: U01DA041106

National Institutes of Health

Grant: U01DA041022

National Institutes of Health

Grant: U01DA051018

National Institutes of Health

Grant: U01DA050989

National Institutes of Health

Grant: U24DA041147

National Institutes of Health

Grant: U01DA041048

National Institutes of Health

Grant: U01DA051038

National Institutes of Health

Grant: U24DA041123

National Institutes of Health

Grant: U01DA050988

National Institutes of Health

Grant: U01DA041148

National Institutes of Health

Grant: U01DA041093

National Institutes of Health

Grant: U01DA041117

National Institutes of Health

Grant: U01DA050987

National Institutes of Health

Grant: U01DA041120

National Institutes of Health

Grant: U01DA041028

National Institutes of Health

Grant: U01DA051039

National Institutes of Health

Grant: U01DA041089

National Institutes of Health

Grant: U01DA041174

National Institutes of Health

Grant: U01DA051037

National Institutes of Health

Grant: U01DA051016

National Institutes of Health

Grant: U01DA041134

National Institutes of Health

Grant: U01DA041025

National Institute on Alcohol Abuse and Alcoholism

Grant: K23AA026890

National Institute on Alcohol Abuse and Alcoholism

Grant: U54AA027989

National Institute on Alcohol Abuse and Alcoholism

Grant: R01AA031959

NIAAA NIH HHS

Grant: K01 AA025670

NIAAA NIH HHS

Grant: R01 AA030971

FWCI

19.06

Citation Percentile

1.0%

Citation Trend

2025

2026

hybridLicense: cc-by

journalhttps://doi.org/10.1016/j.cell.2024.11.012

publisherhttps://doi.org/10.1016/j.cell.2024.11.012

publisherhttps://api.elsevier.com/content/article/PII:S0092867424013291?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S0092867424013291?httpAccept=text/plain

repositoryhttps://pubmed.ncbi.nlm.nih.gov/39706190

Fields of Study

Eating Disorders and BehaviorsHumansWearable Electronic DevicesGenome-Wide Association StudyPhenotypeMental DisordersAdolescentMaleFemaleArtificial Intelligence

MeSH Terms

Wearable Electronic DevicesAdolescentArtificial IntelligenceMental DisordersFemaleHumansMalePhenotypePolymorphism, Single NucleotideGenome-Wide Association Study

Keywords

BiologyWearable computerGeneticsComputational biologyWearable technologyEvolutionary biologyComputer scienceAIGWASbraindeep learningdigital phenotypinggenomicspersonal healthpsychiatrywearable biosensors

Sustainable Development Goals

SDG 0: Gender equality