Cross-Domain Text Mining to Predict Adverse Events from Tyrosine Kinase Inhibitors for Chronic Myeloid Leukemia is a research paper published in Cancers (2022). On theSindex it has a DataRank of 0. It has been cited 22 times.
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.
Georgia Institute of Technology President’s Undergraduate
Grant: 467
Georgia Institute of Technology President’s Undergraduate
Grant: R21CA232249
Georgia Institute of Technology President’s Undergraduate
Grant: 1944247
CAREER: A systems engineering approach to elucidate and treat multi-factorial pathology
National Institutes of Health
Grant: 1R21CA232249-01A1
A Big Data Approach to BCR ABL Leukemias
FWCI
1.41
Citation Percentile
0.8%
Influential Citations
1
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals