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Using machine learning probabilities to identify effects of COVID-19

Patterns(2023)10.1016/j.patter.2023.100889Source: DataRank Database

Using machine learning probabilities to identify effects of COVID-19 is a research paper published in Patterns (2023). On theSindex it has a DataRank of 0.104. It has been cited 1 time.

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0.104DataRank · unranked

Scored on demand from live citation data

Open Access1 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (3 grants)Impact (FWCI 0.15)OA: goldTopics (32)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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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.104

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

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Authors (6)

Undina Gisladottir ORCID,Jenna Kefeli,Yutaro Tanaka ORCID,Benjamin May ORCID,Nicholas P. Tatonetti ORCID

Live enrichment

PubMed:38106616 OpenAlex:https://openalex.org/W4389247382

National Institute of General Medical Sciences

Grant: R35GM131905

National Institutes of Health

Grant: 5R35GM131905-06

Data-driven drug discovery: investigating the molecular mechanisms of safety and efficacy

NLM NIH HHS

Grant: T15 LM007079

FWCI

0.15

Citation Percentile

0.5%

Citation Trend

2024

goldLicense: cc-by

journalhttp://www.cell.com/article/S266638992300291X/pdf

GOLDhttp://www.cell.com/article/S266638992300291X/pdf

publisherhttp://www.cell.com/article/S266638992300291X/pdf

publisherhttps://api.elsevier.com/content/article/PII:S266638992300291X?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S266638992300291X?httpAccept=text/plain

Fields of Study

COVID-19 diagnosis using AICOVID-19 Clinical Research StudiesCOVID-19 epidemiological studiesMedicineComputer Science0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

Coronavirus disease 2019 (COVID-19)Retrospective cohort studyMedicineHealth recordsDiseaseCoronavirusDiabetes mellitusPublic healthSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Random forestIntensive care medicineMyocardial infarctionInfectious disease (medical specialty)Internal medicineArtificial intelligenceHealth careComputer sciencePathologyArticleCOVID-19 effectsalgorithm developmentclinical informaticsmachine learningsurvival analysis

Sustainable Development Goals

SDG 0: Good health and well-being