| 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 | 447 | 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 | 263 | 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 | 78* | 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 | 64 | 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 | 64 | 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 | 42 | 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 | 36 | 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 | 27* | 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 | 25 | 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 | 21 | 2018 |
| Forecasting Internally Displaced Population Migration Patterns in Syria and Yemen BQ Huynh, S Basu Disaster Medicine and Public Health Preparedness, 2019 | 13 | 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 | 13 | 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 | 11 | 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 | 8 | 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 | 6 | 2021 |
Maryellen GigerUniversity of ChicagoZweryfikowany adres z uchicago.edu
