Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients

Dammu, Hongyi, Thomas Ren, and Tim Q Duong. 2023. “Deep Learning Prediction of Pathological Complete Response, Residual Cancer Burden, and Progression-Free Survival in Breast Cancer Patients”. Plos One 18 (1): e0280148.

Last updated on 10/26/2023

Recent Publications

Magnetic resonance imaging detection of deep gray matter iron deposition in multiple sclerosis: A systematic review
An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C)
Deep learning combining FDG-PET and neurocognitive data accurately predicts MCI conversion to Alzheimer s dementia 3-year post MCI diagnosis
Incidence of new-onset hypertension post—COVID-19: comparison with influenza
Machine learning prediction of pathological complete response and overall survival of breast cancer patients in an underserved inner-city population
Deep learning applications to breast cancer detection by magnetic resonance imaging: a literature review

Tim Q Duong, Ph.D.

Professor, Department of Radiology
Professor, Department of Biochemistry
Professor, Department of Ophthalmology & Visual Sciences
Professor, Dominick P. Purpura Department of Neuroscience
Vice Chair for Research Department of Radiology

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Montefiore Medical Center
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tim.duong@einsteinmed.edu
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