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

Utilizing Longitudinal Chest X-Rays and Reports to Pre-fill Radiology Reports

Lecture notes in computer science(2023)10.1007/978-3-031-43904-9_19Source: DataRank Database

Utilizing Longitudinal Chest X-Rays and Reports to Pre-fill Radiology Reports is a research paper published in Lecture notes in computer science (2023). On theSindex it has a DataRank of 0.500. It has been cited 27 times.

N/A

0.500DataRank · unranked

Scored on demand from live citation data

Open Access27 citations

Download PDF

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 (4 grants)OA: greenTopics (12)IDs (PubMed, PMC)

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.

DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.500

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.

Learn more about DataRank methodology →

Authors (6)

Tejas Sudharshan Mathai ORCID,Pritam Mukherjee ORCID,Yifan Peng ORCID,Ronald M. Summers ORCID,ZHIYONG LU ORCID

Live enrichment

PubMed:38501075 PMC:PMC10947431

NLM NIH HHS

Grant: R00 LM013001

NLM NIH HHS

Grant: R01 LM014306

National Institutes of Health

Grant: 5R00LM013001-04

A framework to enhance radiology structured report by invoking NLP and DL: Models and Applications

National Science Foundation

Grant: 2145640

CAREER: Knowledge-enhanced and interpretable radiology report generation

greenLicense: cc-by

repositoryhttps://arxiv.org/pdf/2306.08749

publisherhttps://link.springer.com/content/pdf/10.1007/978-3-031-43904-9_19

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10370215/pdf/nihpp-2306.08749v2.pdf

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10947431/pdf/nihms-1974278.pdf

repositoryhttps://doi.org/10.48550/arxiv.2306.08749

Fields of Study

0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Longitudinal dataChest X-raysRadiology ReportsReport GenerationReport Pre-fillingFOS: Computer and information sciencesComputer Science - Machine LearningComputer Science - Computation and LanguageComputation and Language (cs.CL)Machine Learning (cs.LG)