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High-Throughput Clinical Trial Emulation with Real World Data and Machine Learning: A Case Study of Drug Repurposing for Alzheimer’s Disease

medRxiv(2022)10.1101/2022.01.31.22270132Source: DataRank Database

High-Throughput Clinical Trial Emulation with Real World Data and Machine Learning: A Case Study of Drug Repurposing for Alzheimer’s Disease is a research paper published in medRxiv (2022). On theSindex it has a DataRank of 0.312. It has been cited 7 times.

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0.312DataRank · unranked

Scored on demand from live citation data

Open Access7 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (8 grants)OA: greenTopics (20)IDs (PubMed, OpenAlex)SDGs (2)

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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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.312

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

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Authors (13)

Hao Zhang ORCID,Jie Xu ORCID,Hansi Zhang ORCID,Sajjad Fouladvand ORCID,Shreyas Havaldar ORCID

Live enrichment

PubMed:21097893 OpenAlex:https://openalex.org/W4210350133

National Institutes of Health

Grant: 5R56AG069880-02

Advancing Drug Repositioning for Alzheimer’s Disease using Real-world Data

National Institutes of Health

Grant: 3RF1AG072449-01S1

Identification of Mild Cognitive Impairment using Machine Learning from Language and Behavior Markers

National Institutes of Health

Grant: 5R01CA246418-04

The benefits and harms of lung cancer screening in Florida

National Institutes of Health

Grant: 3R21CA245858-01A1S1

Examine the risk of Alzheimer's disease in sexual and gender minorities

National Institutes of Health

Grant: 1RF1AG059319-01

SYSTEMATIC DRUG REPURPOSING TARGETING IMMUNE ACTIVATION NETWORKS IN ALZHEIMER'S DISEASE (AD)

National Institutes of Health

Grant: 1R21AG068717-01

Optimizing the Population Representativeness of Older Adults in Alzheimer's Disease and Related Dementia Clinical Trials

National Science Foundation

Grant: 1750326

CAREER: Interpretable Deep Modeling of Discrete Time Event Sequences

National Institutes of Health

Grant: 5R01MH124740-04

Developing Suicide Risk Algorithms for Diverse Clinical Settings using Data Fusion

greenLicense: cc-by-nc-nd

repositoryhttps://www.medrxiv.org/content/medrxiv/early/2022/03/10/2022.01.31.22270132.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2022.01.31.22270132

repositoryhttps://doi.org/10.1101/2022.01.31.22270132

https://www.medrxiv.org/content/medrxiv/early/2022/02/01/2022.01.31.22270132.full.pdf

Fields of Study

Statistical Methods in Clinical TrialsHealth Systems, Economic Evaluations, Quality of LifeAdvanced Causal Inference Techniques0101 mathematics01 natural sciences

Keywords

Machine learningRepurposingRandomized controlled trialArtificial intelligenceEmulationDrug repositioningComputer scienceClinical trialMedicineConfoundingPsychologyDrugPharmacologyInternal medicineEngineering

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Industry, innovation and infrastructure