Benjamin Q Huynh
Benjamin Q Huynh
Zweryfikowany adres z stanford.edu - Strona główna
Cytowane przez
Cytowane przez
Digital mammographic tumor classification using transfer learning from deep convolutional neural networks
BQ Huynh, H Li, ML Giger
Journal of Medical Imaging 3 (3), 034501, 2016
A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets
N Antropova, BQ Huynh, ML Giger
Medical physics 44 (10), 5162-5171, 2017
Frequency of routine testing for coronavirus disease 2019 (COVID-19) in high-risk healthcare environments to reduce outbreaks
ET Chin, BQ Huynh, LAC Chapman, M Murrill, S Basu, NC Lo
Clinical Infectious Diseases 73 (9), e3127-e3129, 2020
Deep learning in breast cancer risk assessment: evaluation of convolutional neural networks on a clinical dataset of full-field digital mammograms
H Li, ML Giger, BQ Huynh, NO Antropova
Journal of medical imaging 4 (4), 041304, 2017
MO‐DE‐207B‐06: Computer‐aided diagnosis of breast ultrasound images using transfer learning from deep convolutional neural networks
B Huynh, K Drukker, M Giger
Medical physics 43 (6Part30), 3705-3705, 2016
Routine asymptomatic testing strategies for airline travel during the COVID-19 pandemic: a simulation study
MV Kiang, ET Chin, BQ Huynh, LAC Chapman, I Rodríguez-Barraquer, ...
The Lancet Infectious Diseases 21 (7), 929-938, 2021
SU‐D‐207B‐06: Predicting breast cancer malignancy on DCE‐MRI data using pre‐trained convolutional neural networks
N Antropova, B Huynh, M Giger
Medical physics 43 (6Part4), 3349-3350, 2016
Projected geographic disparities in healthcare worker absenteeism from COVID-19 school closures and the economic feasibility of child care subsidies: a simulation study
ET Chin, BQ Huynh, NC Lo, T Hastie, S Basu
BMC medicine 18 (1), 1-8, 2020
Comparison of breast DCE-MRI contrast time points for predicting response to neoadjuvant chemotherapy using deep convolutional neural network features with transfer learning
BQ Huynh, N Antropova, ML Giger
Medical imaging 2017: computer-aided diagnosis 10134, 207-213, 2017
Breast lesion classification based on dynamic contrast-enhanced magnetic resonance images sequences with long short-term memory networks
N Antropova, B Huynh, H Li, ML Giger
Journal of Medical Imaging 6 (1), 011002, 2018
Forecasting Internally Displaced Population Migration Patterns in Syria and Yemen
BQ Huynh, S Basu
Disaster Medicine and Public Health Preparedness, 2019
Performance comparison of deep learning and segmentation-based radiomic methods in the task of distinguishing benign and malignant breast lesions on DCE-MRI
N Antropova, B Huynh, M Giger
Medical imaging 2017: Computer-aided diagnosis 10134, 369-373, 2017
Recurrent neural networks for breast lesion classification based on DCE-MRIs
N Antropova, B Huynh, M Giger
Medical imaging 2018: Computer-aided diagnosis 10575, 593-598, 2018
Deep learning and three-compartment breast imaging in breast cancer diagnosis
K Drukker, BQ Huynh, ML Giger, S Malkov, JI Avila, B Fan, B Joe, ...
Medical Imaging 2017: Computer-Aided Diagnosis 10134, 363-368, 2017
Public health impacts of an imminent Red Sea oil spill
BQ Huynh, LH Kwong, MV Kiang, ET Chin, AM Mohareb, AO Jumaan, ...
Nature sustainability 4 (12), 1084-1091, 2021
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