Do, Synho

Current Applications and Future Impact of Machine Learning in Radiology

Choy, G., Khalilzadeh, O., Michalski, M., Do, S., Samir, A. E., Pianykh, O. S., Geis, J. R., Pandharipande, P. V., Brink, J. A., & Dreyer, K. J. (2018) · Radiology

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 800

Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success

Thrall, J. H., Li, X., Li, Q., Cruz, C., Do, S., Dreyer, K., & Brink, J. (2018) · Journal of the American College of Radiology

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 710

Fully Automated Deep Learning System for Bone Age Assessment

Lee, H., Tajmir, S., Lee, J., Zissen, M., Yeshiwas, B. A., Alkasab, T. K., Choy, G., & Do, S. (2017) · Journal of Digital Imaging

Forensic Anthropology and Bioarchaeology StudiesMedical Imaging and Analysis

Cited by 452

An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets

Lee, H., Yune, S., Mansouri, M., Kim, M., Tajmir, S. H., Guerrier, C. E., Ebert, S. A., Pomerantz, S. R., Romero, J. M., Kamalian, S., et al. (2018) · Nature Biomedical Engineering

Intracerebral and Subarachnoid Hemorrhage ResearchExplainable Artificial Intelligence (XAI)

Cited by 441

How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?

Cho, J., Lee, K., Shin, E., Choy, G., & Do, S. (2015) · arXiv

Artificial Intelligence in Healthcare and EducationAdvanced Neural Network Applications

Cited by 268

Deep Convolutional Neural Network–based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs

Sim, Y., Chung, M. J., Kotter, E., Yune, S., Kim, M., Do, S., Han, K., Kim, H., Yang, S., Lee, D.-J., et al. (2020) · Radiology

AI in cancer detectionLung Cancer Diagnosis and Treatment

Cited by 248

Tackling prediction uncertainty in machine learning for healthcare

Chua, M., Kim, D., Choi, J., Lee, N. G., Deshpande, V., Schwab, J., Lev, M. H., Gonzalez, R. G., Gee, M. S., & Do, S. (2022) · Nature Biomedical Engineering

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 114