Interactive Machine Learning-Based Multi-Label Segmentation of Solid Tumors and Organs is a research paper published in Applied Sciences (2021). On theSindex it has a DataRank of 0. It has been cited 6 times.
Scored on demand from live citation data
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.
National Institutes of Health
Grant: U24CA189523
National Institutes of Health
Grant: U01CA242871
NINDS NIH HHS
Grant: R01 NS042645
NCI NIH HHS
Grant: P30 CA008748
National Institutes of Health
Grant: 7R01NS042645-02
Modeling/Estimating brain deformation in tumor patients
National Institutes of Health
Grant: 5U01CA242871-02
The Federated Tumor Segmentation (FeTS) platform: An intuitive tool facilitating secure multi-institutional collaboration
National Institutes of Health
Grant: 5U24CA189523-05
Cancer imaging phenomics software suite: application to brain and breast cancer
FWCI
0.63
Citation Percentile
0.7%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals