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

James H. Thrall, Xiang Li, Quanzheng Li et al. · Journal of the American College of Radiology · 2018 · 692 citations

Artificial Intelligence, Biomedical Artificial Intelligence, Engineering +13

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

Hyunkwang Lee, Sehyo Yune, Mohammad Mansouri et al. · Nature Biomedical Engineering · 2018 · 439 citations

Convolutional Neural Network, Engineering, Machine Learning +15

Abdominal CT: Comparison of Adaptive Statistical Iterative and Filtered Back Projection Reconstruction Techniques

Sarabjeet Singh, Mannudeep K. Kalra, Jiang Hsieh et al. · Radiology · 2010 · 437 citations

Fully Automated Deep Learning System for Bone Age Assessment

Hyunkwang Lee, Shahein Tajmir, Jenny Lee et al. · Journal of Digital Imaging · 2017 · 434 citations · Full text

Convolutional Neural Network, Engineering, Machine Learning +22

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

Junghwan Cho, Kyewook Lee, Ellie Shin et al. · arXiv (Cornell University) · 2015 · 276 citations · Full text

Convolutional Neural Network, Engineering, Machine Learning +24