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Open and reusable deep learning for pathology with WSInfer and QuPath

npj Precision Oncology(2024)10.1038/s41698-024-00499-9Source: DataRank Database

Open and reusable deep learning for pathology with WSInfer and QuPath is a research paper published in npj Precision Oncology (2024). On theSindex it has a DataRank of 0. It has been cited 25 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access25 citations

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Linked data & code

Open and reusable deep learning for pathology with WSInfer and QuPath · arXiv

doi

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (7 grants)Impact (FWCI 5.83)OA: goldTopics (27)Linked Datasets (1)DataCite Reuse (1)IDs (PubMed, PMC, OpenAlex)Annotations (1)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

DataCite relations
Linked datasets

Reusable (0/3)

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Authors (9)

Alan O’Callaghan ORCID,Fiona Inglis ORCID,Swarad Gat ORCID,Tahsin Kurç ORCID,Rajarsi Gupta ORCID

Live enrichment

PubMed:38200147 PMC:PMC10781748 OpenAlex:https://openalex.org/W4390705971

Wellcome Trust

Grant: 223750

QuPath: Advanced open platform for next generation bioimage analysis

Wellcome Trust

Grant: 223750/Z/21/Z

NIGMS NIH HHS

Grant: T32 GM008444

Wellcome Trust

Grant: unidentified

unidentified

National Institutes of Health

Grant: 2T32GM008444-24

Medical Scientist Training Program

Stony Brook Provost ProFund 2022 award; the generosity of Bob Beals and Betsy Barton.

Stony Brook Provost ProFund 2022 award; the generosity of Bob Beals and Betsy Barton

FWCI

5.83

Citation Percentile

1.0%

Citation Trend

2024

2025

2026

goldLicense: cc-by

journalhttps://www.nature.com/articles/s41698-024-00499-9.pdf

journalhttps://doi.org/10.1038/s41698-024-00499-9

repositoryhttps://pubmed.ncbi.nlm.nih.gov/38200147

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/10781748

repositoryhttps://doaj.org/article/b7fa4472c6fb4be3a533684d16da2307

Fields of Study

AI in cancer detectionRadiomics and Machine Learning in Medical ImagingCancer Genomics and Diagnostics0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

Digital pathologyComputer scienceDeep learningReuseArtificial intelligenceOpen sourceSoftwarePathologyData scienceMedicineEngineeringOperating systemFOS: Computer and information sciencesComputer Vision and Pattern Recognition (cs.CV)FOS: Biological sciencesComputer Science - Computer Vision and Pattern RecognitionNeoplasms. Tumors. Oncology. Including cancer and carcinogensQuantitative Biology - Tissues and OrgansBrief CommunicationTissues and Organs (q-bio.TO)RC254-282

Sustainable Development Goals

SDG 0: Life in Land

Open and reusable deep learning for pathology with WSInfer and QuPath

10.48550/arxiv.2309.04631arXiv

Open and reusable deep learning for pathology with WSInfer and QuPath

FAIR Checklist

Authors (9)

Funding (7 grants)

Impact

Open Access

Topics

Linked Datasets (1)

Annotations (Europe PMC)