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

Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study

Cancer Cell(2023)10.1016/j.ccell.2023.08.002Source: DataRank Database

Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study is a research paper published in Cancer Cell (2023). On theSindex it has a DataRank of 4.8. It has been cited 254 times, with 200 citing works in its 1-hop citation network.

N/A

4.8DataRank · unranked

Scored on demand from live citation data

Open Access254 citations · 200 citing works in its network

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 (54 grants)OA: hybridTopics (29)IDs (PubMed, PMC)Annotations (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.

DataRank Breakdown

Base Score 17%Citation Network 83%

Base Score Contribution

0.831

From this paper's citation signal

Citation Network Contribution

4.0

From 136 citing papers with measurable signal

Learn more about DataRank methodology →

Top 5 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 200 citers.

Deep learning transforms colorectal cancer biomarker prediction from histopathology images
Cancer Cell202312 citations11 referencesContributes 0.233
THItoGene: a deep learning method for predicting spatial transcriptomics from histological images
Briefings in Bioinformatics2023120 citations40 referencesContributes 0.120
CAMIL: channel attention-based multiple instance learning for whole slide image classification
Bioinformatics202515 citations25 referencesContributes 0.111
Pathology-based deep learning features for predicting basal and luminal subtypes in bladder cancer
BMC Cancer202515 citations25 referencesContributes 0.111
A pathology foundation model for cancer diagnosis and prognosis prediction
Nature2024458 citations63 referencesContributes 0.097

Authors (67)

Daniel Reisenbüchler ORCID,Nicholas P. West ORCID,Jan Niehues ORCID,Jiefu Zhu ORCID,Sebastian Foersch ORCID

Live enrichment

PubMed:37652006 PMC:PMC10507381

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Grant: 184.021.007

BBMRI-NL