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JCO Clinical Cancer Informatics|May 6, 2022
Machine Learning to Predict Risk of Relapse Using Cytologic Image Markers in Patients With Acute Myeloid Leukemia Posthematopoietic Cell TransplantationSara Arabyarmohammadi, Patrick Leo, Vidya Sankar Viswanathan, et al.
JCO Clinical Cancer Informatics|October 15, 2020
Tailoring Therapy for Children With Neuroblastoma on the Basis of Risk Group Classification: Past, Present, and FutureWayne H Liang, Sara M Federico, Wendy B London, et al.
JCO Clinical Cancer Informatics|April 2, 2020
Integrated Informatics Analysis of Cancer-Related VariantsKymberleigh A Pagel, Rick Kim, Kyle Moad, et al.
JCO Clinical Cancer Informatics|January 13, 2021
Machine Learning Frameworks to Predict Neoadjuvant Chemotherapy Response in Breast Cancer Using Clinical and Pathological FeaturesNicholas Meti, Khadijeh Saednia, Andrew Lagree, et al.
JCO Clinical Cancer Informatics|January 13, 2023
Patterns of Health Portal Use by Regular Portal Users Among Patients With Cancer: Results From the UWCCC Survivorship ProgramHamid Emamekhoo, Thevaa Chandereng, Mary E Sesto, et al.
JCO Clinical Cancer Informatics|January 3, 2023
Electronic Consent at US Cancer Centers: A Survey of Practices, Challenges, and OpportunitiesSusan Chimonas, Allison Lipitz-Snyderman, Kemi Gaffney, et al.
JCO Clinical Cancer Informatics|December 21, 2022
Predicting In-Hospital Mortality After Acute Myeloid Leukemia Therapy: Through Supervised Machine Learning AlgorithmsNauman S Siddiqui, Andreas Klein, Amandeep Godara, et al.
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