Randomized Clinical Trials of Artificial Intelligence.

[1]  Yuri Kotliarov,et al.  Unsupervised analysis of transcriptomic profiles reveals six glioma subtypes. , 2009, Cancer research.

[2]  Aldo A. Faisal,et al.  The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care , 2018, Nature Medicine.

[3]  M. P. Mulder,et al.  Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial. , 2020, JAMA.

[4]  R. Bellman.  Dynamic programming. , 1957, Science.

[5]  M. Abràmoff,et al.  Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices , 2018, npj Digital Medicine.

[6]  Robert M Wachter,et al.  Artificial Intelligence in Health Care: Will the Value Match the Hype? , 2019, JAMA.

[7]  T. Scheeren,et al.  Ability of an Arterial Waveform Analysis–Derived Hypotension Prediction Index to Predict Future Hypotensive Events in Surgical Patients , 2020, Anesthesia and analgesia.

[8]  T. Weiser,et al.  Evaluating the collection, comparability and findings of six global surgery indicators , 2018, The British journal of surgery.

[9]  Subhashini Venugopalan,et al.  Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. , 2016, JAMA.

[10]  Philip R. O. Payne,et al.  Questions for Artificial Intelligence in Health Care. , 2019, JAMA.

[11]  J. Rinehart,et al.  Machine-learning Algorithm to Predict Hypotension Based on High-fidelity Arterial Pressure Waveform Analysis , 2018, Anesthesiology.

[12]  Ravi B. Parikh,et al.  Addressing Bias in Artificial Intelligence in Health Care. , 2019, JAMA.

[13]  Geoffrey E. Hinton.  Deep Learning-A Technology With the Potential to Transform Health Care. , 2018, JAMA.