The Future of Medicine and Medical Care co-created with AI and Human
Author:
Affiliation:
1. Department of Artificial Intelligence Medicine, Graduate School of Medicine, Chiba University
2. Medical Data Mathematical Reasoning Team, Advanced Data Science Project (ADSP), RIKEN Information R&D and Strategy Headquarters
Publisher
Medical Association of Nippon Medical School
Link
https://www.jstage.jst.go.jp/article/manms/19/4/19_350/_pdf
Reference14 articles.
1. 1. Esteva A, Kuprel B, Novoa R, et al.: Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017; 542: 115-118.
2. 2. Tomašev N, Glorot X, Rae J, et al.: A clinically applicable approach to continuous prediction of future acute kidney injury. Nature 2019; 572: 116-119.
3. 3. Ardila D, Kiraly A, Bharadwaj S, et al.: End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nature Medicine 2019; 25: 954-961.
4. 4. Davis S, Lasko T, Chen G, Siew ED, Matheny ME: Calibration drift in regression and machine learning models for acute kidney injury. J Am Med Inform Assoc 2017; 24: 1052-1061.
5. 5. Goodfellow I, Shlens J, Szegedy C: Explaining and Harnessing Adversarial Examples. arXiv 2015. doi: https://doi.org/10.48550/arXiv.1412.6572
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