Combining Biology-based and MRI Data-driven Modeling to Predict Response to Neoadjuvant Chemotherapy in Patients with Triple-Negative Breast Cancer is a research paper published in Radiology Artificial Intelligence (2024). On theSindex it has a DataRank of 0.355. It has been cited 8 times, with 6 citing works in its 1-hop citation network.
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Linked data & code
Repositories this paper deposited data in (declared in PubMed).
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Base Score Contribution
0.330
From this paper's citation signal
Citation Network Contribution
0.0253
From 2 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 6 citers.
National Cancer Institute
Grant: U01CA142565, U01CA174706, and U24CA226110
National Science Foundation
Grant: 2019844
AI Institute: Institute for Foundations of Machine Learning
National Science Foundation Graduate Research Fellowship Program
Grant: DE2137420
NCI NIH HHS
Grant: U24 CA226110
National Science Foundation
Grant: IFML 2019844
NCI NIH HHS
Grant: U01 CA174706
NCI NIH HHS
Grant: U01 CA142565
Conquer Cancer Foundation
Robert D. Moreton Distinguished Chair Funds in Diagnostic Radiology
The University of Texas MD Anderson Cancer Center Moon Shots Program
Joint Center for Computational Oncology
Susan Papizan Dolan Fellowship in Breast Oncology
Winterhof Fund
The Stillwater Medical Foundation
CPRIT Scholar in Cancer Research
Shari Sella Memorial Fund
Allison and Brian Grove Endowed Fellowship for Breast Medical Oncology
Gayle Monroe Kuoni Breast Medical Oncology Research Endowment
Suzanne Potter ARTEMIS Fund
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