Improving the Generalizability of Deep Learning for T2-Lesion Segmentation of Gliomas in the Post-Treatment Setting is a research paper published in Bioengineering (2024). On theSindex it has a DataRank of 0.
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: P01CA118816
National Institutes of Health
Grant: HT9425-23-1-0510
National Institutes of Health
Grant: HT9425-23-1-0511
National Institutes of Health
Grant: HT9425-23-1-0512
Department of Defense
Grant: HT9425-23-1-0510, HT9425-23-1-0511, HT9425-23-1-0512
UCSF Helen Diller Family Cancer Center Cancer
Grant: Imaging Resources Pilot Grant
NCI NIH HHS
Grant: T32 CA151022
National Institutes of Health
Grant: 3P01CA118816-14S1
Noninvasive Metabolic Signatures to Improve Management of Molecular Subtypes of Glioma
FWCI
0.00
Citation Percentile
0.1%
Fields of Study
Keywords