Radiomic predicts early response to CDK4/6 inhibitors in hormone receptor positive metastatic breast cancer
Mohammadhadi Khorrami(Case Western Reserve University), Anant Madabhushi(Emory University), Siddharth Kunte(Toledo Clinic Cancer Center), Nathaniel Braman(Tempus Labs (United States)), Jame Abraham(Cleveland Clinic), Vidya Sakar Viswanathan(Emory University), Alberto J. Montero(University Hospitals Seidman Cancer Center), Priyanka Reddy(University Hospitals Seidman Cancer Center), Amit Gupta(University of Washington)
Cited by 13
Related Papers
Predicting cancer outcomes with radiomics and artificial intelligence in radiology
|Nature Reviews Clinical Oncology|2021|810
Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update
|Radiology Artificial Intelligence|2024|406
Association of Bariatric Surgery With Cancer Risk and Mortality in Adults With Obesity
|JAMA|2022|324
Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non–Small Cell Lung Cancer
|Cancer Immunology Research|2019|313
Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer
|npj Breast Cancer|2020|208