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

Unsupervised Black-Box Model Domain Adaptation for Brain Tumor Segmentation

Frontiers in Neuroscience(2022)10.3389/fnins.2022.837646Source: DataRank Database

Unsupervised Black-Box Model Domain Adaptation for Brain Tumor Segmentation is a research paper published in Frontiers in Neuroscience (2022). On theSindex it has a DataRank of 0. It has been cited 15 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access15 citations

Download PDF

Cite:

Linked data & code

doi

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 (3 grants)Impact (FWCI 1.74)OA: goldTopics (22)IDs (PubMed, PMC, OpenAlex)Annotations (1)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 (7)

Chaehwa Yoo ORCID,Fangxu Xing ORCID,C.‐C. Jay Kuo ORCID,Georges El Fakhri ORCID,Je‐Won Kang ORCID

Live enrichment

PubMed:35720708 PMC:PMC9201342 OpenAlex:https://openalex.org/W4281710060

National Institutes of Health

Grant: P41EB022544

National Institutes of Health

Grant: R01DC018511

NCI NIH HHS

Grant: R01 CA165221

FWCI

1.74

Citation Percentile

0.9%

Citation Trend

2022

2023

2024

2025

2026

goldLicense: cc-by

journalhttps://www.frontiersin.org/articles/10.3389/fnins.2022.837646/pdf

publisherhttps://www.frontiersin.org/articles/10.3389/fnins.2022.837646/pdf

publisherhttps://www.frontiersin.org/articles/10.3389/fnins.2022.837646/full

journalhttps://doi.org/10.3389/fnins.2022.837646

repositoryhttps://pubmed.ncbi.nlm.nih.gov/35720708

Fields of Study

Domain Adaptation and Few-Shot LearningCOVID-19 diagnosis using AIBrain Tumor Detection and Classification

Keywords

Computer scienceSegmentationArtificial intelligenceDomain adaptationMachine learningTransfer of learningDomain (mathematical analysis)Entropy (arrow of time)Black boxLabeled dataUnsupervised learningPattern recognition (psychology)Data miningClassifier (UML)Brain tumorMr ImageBlack-box ModelUnsupervised Domain AdaptationKnowledge Distillation

Sustainable Development Goals

SDG 0: Partnerships for the goals