Reproducible Machine Learning Methods for Lung Cancer Detection Using Computed Tomography Images: Algorithm Development and Validation is a research paper published in Journal of Medical Internet Research (2020). On theSindex it has a DataRank of 4.0. It has been cited 78 times, with 72 citing works in its 1-hop citation network.
Scored on demand from live citation data
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.655
From this paper's citation signal
Citation Network Contribution
3.4
From 51 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 72 citers.
NIH HHS
Grant: OT3 OD025466
National Institutes of Health
Grant: 1OT3OD025466-01
Patient-Centric Information Commons under FAIR Principles (PIC-FAIR)
FWCI
5.70
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks
Additional file 1 of Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks
Additional file 2 of Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks
Additional file 2 of Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks