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Overview : How Artificial Intelligence Will Improve Health -- Randomization : The "Secret Sauce" -- Evaluation : The Facts Matter. Pseudo-Innovation vs Real Innovation -- Synergy : Building a Successful Clinician-Computer Collaboration -- Fairness : Addressing the Ethical, Regulatory, and Privacy Issues -- Modeling : An Overview of Predictive Modeling, Neural Networks, and Deep Learning -- EHRs : Exporting, Cleaning, Managing Datasets, and Integrating Models into the Electronic Health Record -- Resistance : Understanding and Overcoming the Resistance to AI, Randomization, and Change -- Execution : Increasing the Odds of Future Success -- Integration : Building a Learning Health Care System With Pragmatic AI Trials -- Streamlining : Reducing Waste and Lowering Costs in Health Care -- Complications : Predicting and Preventing Hospital Complications -- Prevention : Identifying Diseases With Predictive Models -- Precision Medicine : AI to Improve Health Screenings and Treatments -- Drugs and Devices : Using AI to Improve Pharmaceutical and Medical Device Development and Applications -- Medical Literature : AI and Information Overload -- Imaging : Medical Imaging and Strategies for Assessing Patient Impact -- Pandemics : Using AI Tools to Improve Health Outcomes in a Pandemic -- Careers : How to Build a Career Around AI in Medicine by Turning This Playbook Into a Reality. |