Breast Multiparametric MRI for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: The BMMR2 Challenge is a dataset published in Radiology Imaging Cancer (2024). On theSindex it has a DataRank of 0.878, placing it in the top 23% of the data-sharing corpus. It has been cited 25 times, with 19 citing works in its 1-hop citation network.
Ranks in the top 23% for downstream scientific impact
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?
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Base Score Contribution
0.489
From this paper's citation signal
Citation Network Contribution
0.389
From 13 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 19 citers.
National Institutes of Health
Grant: U01 CA225427
National Institutes of Health
Grant: R01 CA132870
National Institutes of Health
Grant: U01 CA180820
National Institutes of Health
Grant: U01 CA180794
National Institutes of Health
Grant: R01 CA248192
National Institutes of Health
Grant: 5R01CA197000-05
Multi-parametric 4-D Imaging Biomarkers for Neoadjuvant Treatment Response
National Institutes of Health
Grant: 5P30CA006973
National Institutes of Health
Grant: U01CA140204
National Institutes of Health
Grant: U24CA226110
National Institutes of Health
Grant: U01CA142565
National Institutes of Health
Grant: U01CA174706
Defense Advanced Research Projects Agency
Grant: HR00112190130
Cancer Prevention and Research Institute of Texas
Grant: RR160005
National Institutes of Health
Grant: 5U01CA140204-03
Multi-Modality Quantitiative Imaging for Evaluation of Response to Cancer Therapy
National Institutes of Health
Grant: 5U01CA142565-05
PET-MRI for Assessing Treatment Response in Breast Cancer Clinical Trials
National Institutes of Health
Grant: 5U01CA225427-02
Quantitative Imaging for Assessing Breast Cancer Response to Treatment
National Institutes of Health
Grant: 5R01CA248192-02
Multicenter Quantitative MRI Assessment of Breast Cancer Therapy Response
National Institutes of Health
Grant: 3P30CA006973-53S2
Regional Oncology Research Center
National Institutes of Health
Grant: 5R01HL149742-02
MRI based phosphocreatine mapping method to assess patients with peripheral arterial disease.
National Institutes of Health
Grant: 5U01DK127400-05
Clinical, Radiologic and Biochemical Factors Related to Diabetes Development after Acute Pancreatitis
National Institutes of Health
Grant: 3U24CA180803-06S1
Imaging and Radiation Oncology Core (IROC) Group
National Institutes of Health
Grant: 5R01CA132870-10
Real-time In Vivo MRI Biomarkers for Breast Cancer Pre-Operative Treatment Trials
National Institutes of Health
Grant: 3U10CA180820-02S3
ECOG-ACRIN Operations Center
National Institutes of Health
Grant: 5U01CA174706-03
Image Driven Multi-Scale Modeling to Predict Treatment Response in Breast Cancer
National Institutes of Health
Grant: 5U24CA226110-05
INTEGRATING OMICS AND QUANTITATIVE IMAGING DATA IN CO-CLINICAL TRIALS TO PREDICT TREATMENT RESPONSE IN TRIPLE NEGATIVE BREAST CANCER
Fields of Study
Keywords
Sustainable Development Goals
Additional file 1 of Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity
Additional file 1 of Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity
ACRIN 6698/I-SPY2 Breast DWI