Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

DR-VIDAL -- Doubly Robust Variational Information-theoretic Deep Adversarial Learning for Counterfactual Prediction and Treatment Effect Estimation on Real World Data

arXiv (Cornell University)(2023)10.48550/arxiv.2303.04201Source: DataRank Database

DR-VIDAL -- Doubly Robust Variational Information-theoretic Deep Adversarial Learning for Counterfactual Prediction and Treatment Effect Estimation on Real World Data is a research paper published in arXiv (Cornell University) (2023). On theSindex it has a DataRank of 0.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access0 citations

Free full text

Cite:

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (6 grants)OA: greenTopics (26)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)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (5)

Feng, Zheng,Jiang Bian ORCID,Kevin Butler ORCID,Mattia Prosperi ORCID,Shantanu Ghosh ORCID

Live enrichment

PubMed:19276002 OpenAlex:https://openalex.org/W4323697692

National Institutes of Health

Grant: 5R01AG076234-03

Computational Drug Repurposing for AD/ADRD with Integrative Analysis of Real World Data and Biomedical Knowledge

National Institutes of Health

Grant: 3R21CA245858-01A1S1

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

National Institutes of Health

Grant: 5R01AI145552-02

Forecasting trajectories of HIV transmission networks with a novel phylodynamic and deep learning framework

National Institutes of Health

Grant: 5R56AG069880-02

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

National Science Foundation

Grant: 2028221

RAPID: Dynamic Identification of SARS-COV-2 Transmission Epicenters in Presence of Spatial Heterogeneity (COV-DYNAMITE)

National Institutes of Health

Grant: 5R01CA246418-04

The benefits and harms of lung cancer screening in Florida

greenLicense: cc-by

repositoryhttps://arxiv.org/pdf/2303.04201

repositoryhttp://arxiv.org/abs/2303.04201

repositoryhttps://doi.org/10.48550/arxiv.2303.04201

https://dx.doi.org/10.48550/arxiv.2303.04201

https://pubmed.ncbi.nlm.nih.gov/37128454

Fields of Study

Machine Learning in HealthcareExplainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Computer scienceMachine learningArtificial intelligenceCounterfactual thinkingAutoencoderRobustness (evolution)Deep learningCausal inferenceGenerative grammarDiscriminative modelEconometricsMathematicsPsychologyCausalityMethodology (stat.ME)FOS: Computer and information sciencesMethodologyHumansElectronic Health RecordsPrognosisMachine Learning (cs.LG)

Sustainable Development Goals

SDG 3: 3. Good health