Daniel Tse
Google (United States)(US)
Publications by Year
Research Areas
Radiomics and Machine Learning in Medical Imaging, COVID-19 diagnosis using AI, Lung Cancer Diagnosis and Treatment, Artificial Intelligence in Healthcare and Education, Tuberculosis Research and Epidemiology
Most-Cited Works
- → International evaluation of an AI system for breast cancer screening(2020)2,977 cited
- → End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography(2019)1,986 cited
- → Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation(2019)280 cited
- → Deep Learning Detection of Active Pulmonary Tuberculosis at Chest Radiography Matched the Clinical Performance of Radiologists(2022)68 cited
- → Author Correction: End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography(2019)65 cited
- → Simplified Transfer Learning for Chest Radiography Models Using Less Data(2022)54 cited
- → Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19(2021)52 cited
- → Development of a Machine Learning Model for Sonographic Assessment of Gestational Age(2023)37 cited
- → A mobile-optimized artificial intelligence system for gestational age and fetal malpresentation assessment(2022)37 cited
- → Addendum: International evaluation of an AI system for breast cancer screening(2020)37 cited