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Artificial Intelligence for Improved Patient Outcomes

Principles for Moving Forward with Rigorous Science
Edition: 1
9781975197933
ISBN/ISSN:
9781975197933
Publication Date:
March 29, 2023
2023-03-29
9781975197933
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Artificial Intelligence for Improved Patient Outcomes provides new, relevant, and practical information on what AI can do in healthcare and ...
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  • Artificial Intelligence for Improved Patient Outcomes provides new, relevant, and practical information on what AI can do in healthcare and how to assess whether AI is improving health outcomes.  
     

    With clear insights and a balanced approach, this innovative book offers a one-stop guide on how to design and lead pragmatic real-world AI studies that yield rigorous scientific evidence—all in a manner that is safe and ethical. Daniel Byrne, Director of Artificial Intelligence Research at AVAIL (the Advanced Vanderbilt Artificial Intelligence Laboratory) and author of landmark pragmatic studies published in leading medical journals, shares four decades of experience as a biostatistician and AI researcher. Building on his first book, Publishing Your Medical Research, the author gives the reader the competitive advantage in creating reproducible AI research that will be accepted in prestigious high-impact medical journals.

    • Provides easy-to-understand explanations of the key concepts in using and evaluating AI in medicine.  

    • Offers practical, actionable guidance on the mechanics and implementation of AI applications in medicine. 

    • Shares career guidance on a successful future in AI in medicine. 

    • Teaches the skills to evaluate AI tools and avoid being misled by the hype. 

    • For a wide audience of healthcare professionals impacted by Artificial Intelligence in medicine, including physician-scientists, AI developers, entrepreneurs, and healthcare leaders who need to evaluate AI applications designed to improve safety, quality, and value for their institutions.  
       

      Enrich Your eBook Reading Experience 
       

    • Read directly on your preferred device(s), such as computer, tablet, or smartphone. 

    • Easily convert to audiobook, powering your content with natural language text-to-speech. 

  • Edition
    1
    ISBN/ISSN
    9781975197933
    Product Format
    Paperback Book
    Trim Size
    7 x 10
    Pages
    266
    Edition
    1
    Publication Date
    March 29, 2023
    Weight
    0.75
  • DANIEL W. BYRNE
  • Contents
    Preface vii
    Acknowledgments ix
    About the Author xiii
    PART I: The Big Picture 1
    CHAPTER I Overview—How Artificial Intelligence Will
    Improve Health 3
    CHAPTER 2 Randomization—The “Secret Sauce” 19
    CHAPTER 3 Evaluation—The Facts Matter. Pseudo- Innovation vs
    Real Innovation 37
    CHAPTER 4 Synergy—Building a Successful Clinician- Computer
    Collaboration 73
    CHAPTER 5 Fairness—Addressing the Ethical, Regulatory,
    and Privacy Issues 87
    PART II: The Mechanics 99
    CHAPTER 6 Modeling—An Overview of Predictive Modeling,
    Neural Networks, and Deep Learning 101
    CHAPTER 7 EHRs—Exporting, Cleaning, Managing Datasets,
    and Integrating Models into the Electronic Health
    Record 121
    PART III: The Implementation 135
    CHAPTER 8 R esistance—Understanding and Overcoming the
    Resistance to AI, Randomization, and Change 137
    CHAPTER 9 Execution—Increasing the Odds of Future Success 147
    CHAPTER 10 Integration—Building a Learning Health Care
    System With Pragmatic AI Trials 157
    CHAPTER 11 Streamlining—Reducing Waste and Lowering
    Costs in Health Care 165PART IV: The Specific Applications 171
    CHAPTER 12 Complications—Predicting and Preventing
    Hospital Complications 173
    CHAPTER 13 Prevention—Identifying Diseases With Predictive
    Models 183
    CHAPTER 14 Precision Medicine—AI to Improve Health
    Screenings and Treatments 189
    CHAPTER 15 Drugs and Devices—Using AI to Improve
    Pharmaceutical and Medical Device Development
    and Applications 197
    CHAPTER 16 Medical Literature—AI and Information Overload 203
    CHAPTER 17 Imaging—Medical Imaging and Strategies for
    Assessing Patient Impact 213
    CHAPTER 18 Pandemics—Using AI Tools to Improve Health
    Outcomes in a Pandemic 221
    PART V: The Future 229
    CHAPTER 19 Careers—How to Build a Career Around AI in
    Medicine by Turning This Playbook Into a Reality 231
    Index 249
    • Provides easy-to-understand explanations of the key concepts in using and evaluating AI in medicine.  

    • Offers practical, actionable guidance on the mechanics and implementation of AI applications in medicine. 

    • Shares career guidance on a successful future in AI in medicine. 

    • Teaches the skills to evaluate AI tools and avoid being misled by the hype. 

    • For a wide audience of healthcare professionals impacted by Artificial Intelligence in medicine, including physician-scientists, AI developers, entrepreneurs, and healthcare leaders who need to evaluate AI applications designed to improve safety, quality, and value for their institutions.  
       

      Enrich Your eBook Reading Experience 

    • Read directly on your preferred device(s), such as computer, tablet, or smartphone. 

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