Paul Cerrato, John Halamka
Reinventing Clinical Decision Support
Data Analytics, Artificial Intelligence, and Diagnostic Reasoning
Paul Cerrato, John Halamka
Reinventing Clinical Decision Support
Data Analytics, Artificial Intelligence, and Diagnostic Reasoning
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The book explains to physicians and technologists the value and limitations of artificial intelligence in the management of disease. Specifically, it explains how machine learning and new types of data analysis will improve diagnosis and personalize patient care.
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The book explains to physicians and technologists the value and limitations of artificial intelligence in the management of disease. Specifically, it explains how machine learning and new types of data analysis will improve diagnosis and personalize patient care.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 184
- Erscheinungstermin: 2. August 2021
- Englisch
- Abmessung: 234mm x 155mm x 15mm
- Gewicht: 376g
- ISBN-13: 9781032081854
- ISBN-10: 1032081856
- Artikelnr.: 62150788
- Verlag: Taylor & Francis
- Seitenzahl: 184
- Erscheinungstermin: 2. August 2021
- Englisch
- Abmessung: 234mm x 155mm x 15mm
- Gewicht: 376g
- ISBN-13: 9781032081854
- ISBN-10: 1032081856
- Artikelnr.: 62150788
Paul Cerrato, MA, has more than 30 years of experience working in healthcare as a medical journalist, research analyst, clinician, and educator. He has written extensively on clinical medicine, clinical decision support, electronic health records, protected health information security, and practice management. He has served as the Editor of InformationWeek Healthcare, Executive Editor of Contemporary OB/GYN, Senior Editor of RN Magazine, and contributing writer/editor for the Yale University School of Medicine, the American Academy of Pediatrics, InformationWeek, Medscape, Healthcare Finance News, IMedicalapps.com, and MedpageToday. The Health Information Management Systems Society (HIMSS) has listed Mr. Cerrato as one of the most influential columnists in healthcare IT. He has served as a guest lecturer or faculty member at the Columbia University College of Physicians and Surgeons, Harvard Medical School, and Vermont College. Among his achievements are 6 editorial awards from the American Business Media-often referred to as the Pulitzer Prize of business journalism-and the Gold Award from the American Society of Healthcare Publications Editors for best signed editorial. John D. Halamka, MD, MS, president of the Mayo Clinic Platform, leads a portfolio of new digital platform businesses focused on transforming health by leveraging artificial intelligence, machine learning, and an ecosystem of partners for the Mayo Clinic. He is a practicing emergency medicine physician. Previously, Dr. Halamka was executive director of the Health Technology Exploration Center for Beth Israel Lahey Health in Massachusetts. Previously, he was chief information officer at Beth Israel Deaconess Medical Center for more than 20 years. In addition, he was the International Healthcare Innovation Professor at Harvard Medical School. As the leader for innovation at the $7 billion Beth Israel Lahey Health, he oversaw digital health relationships with industry, academia, and government worldwide. As a Harvard Medical School professor, he served the George W. Bush administration, the Obama administration, and governments around the world planning their health care information (IT) strategies.
Dedication
Contents
Preface
About the Authors
Chapter 1: Clinical Reasoning and Diagnostic Errors
Chapter 2: The Promise of Artificial Intelligence and Machine Learning
Chapter 3: AI Criticisms, Obstacles, and Limitations
Chapter 4: CDS Systems: Past, Present, and Future
Chapter 5: Reengineering Data Analytics
Chapter 6: Will Systems Biology Transform Clinical Decision Support?
Chapter 7: Precision Medicine
Chapter 8: Reinventing Clinical Decision Support: Case Studies
Index
Contents
Preface
About the Authors
Chapter 1: Clinical Reasoning and Diagnostic Errors
Chapter 2: The Promise of Artificial Intelligence and Machine Learning
Chapter 3: AI Criticisms, Obstacles, and Limitations
Chapter 4: CDS Systems: Past, Present, and Future
Chapter 5: Reengineering Data Analytics
Chapter 6: Will Systems Biology Transform Clinical Decision Support?
Chapter 7: Precision Medicine
Chapter 8: Reinventing Clinical Decision Support: Case Studies
Index
Dedication
Contents
Preface
About the Authors
Chapter 1: Clinical Reasoning and Diagnostic Errors
Chapter 2: The Promise of Artificial Intelligence and Machine Learning
Chapter 3: AI Criticisms, Obstacles, and Limitations
Chapter 4: CDS Systems: Past, Present, and Future
Chapter 5: Reengineering Data Analytics
Chapter 6: Will Systems Biology Transform Clinical Decision Support?
Chapter 7: Precision Medicine
Chapter 8: Reinventing Clinical Decision Support: Case Studies
Index
Contents
Preface
About the Authors
Chapter 1: Clinical Reasoning and Diagnostic Errors
Chapter 2: The Promise of Artificial Intelligence and Machine Learning
Chapter 3: AI Criticisms, Obstacles, and Limitations
Chapter 4: CDS Systems: Past, Present, and Future
Chapter 5: Reengineering Data Analytics
Chapter 6: Will Systems Biology Transform Clinical Decision Support?
Chapter 7: Precision Medicine
Chapter 8: Reinventing Clinical Decision Support: Case Studies
Index