Explainable AI in Healthcare and Medicine (eBook)

Building a Culture of Transparency and Accountability
Artikelnummer: 978-3-030-53352-6
Einband: PDF
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
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This book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Featuring selected papers from the 2020 Health Intelligence Workshop, held as part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference, it offers an overview of the issues, challenges, and opportunities in the field, along with the latest research findings. Discussing a wide range of practical applications, it makes the emerging topics of digital health and explainable AI in health care and medicine accessible to a broad readership. The availability of explainable and interpretable models is a first step toward building a culture of transparency and accountability in health care. As such, this book provides information for scientists, researchers, students, industry professionals, public health agencies, and NGOs interested in the theory and practice of computational models of public and personalized health intelligence.

This book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Featuring selected papers from the 2020 Health Intelligence Workshop, held as part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference, it offers an overview of the issues, challenges, and opportunities in the field, along with the latest research findings. Discussing a wide range of practical applications, it makes the emerging topics of digital health and explainable AI in health care and medicine accessible to a broad readership. The availability of explainable and interpretable models is a first step toward building a culture of transparency and accountability in health care. As such, this book provides information for scientists, researchers, students, industry professionals, public health agencies, and NGOs interested in the theory and practice of computational models of public and personalized health intelligence.

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VerlagSpringer International Publishing
EinbandPDF
Erscheinungsjahr2020
Seitenangabe344 S.
AusgabekennzeichenEnglisch
AbbildungenXXII, 344 p. 110 illus., 84 illus. in color.
Masse12'348 KB
PlattformPDF
ReiheStudies in Computational Intelligence; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics
AutorShaban-Nejad, Arash (Hrsg.) / Michalowski, Martin (Hrsg.) / Buckeridge, David L. (Hrsg.)

Alle Bände der Reihe "Studies in Computational Intelligence; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics (R0)"

Über den Autor Arash (Hrsg.) Shaban-Nejad

Dr. Arash Shaban-Nejad is a leading expert in population and precision health informatics. He is currently an Associate Professor and Director of Population and Precision Health at the UTHSC-Oak Ridge National Laboratory Center for Biomedical Informatics, Department of Pediatrics, University of Tennessee Health Science Center. Dr. Shaban-Nejad received his PhD and MSc in Computer Science from Concordia University, Canada, and an MPH from UC Berkeley, along with post-doctoral training at McGill University and additional training at Harvard School of Public Health. His interdisciplinary research focuses on health AI, explainable AI, large language models, predictive modeling, epidemiologic surveillance, and causal reasoning. He has published extensively, and his research has been funded by several federal, state, and international funding agencies. Dr. Shaban-Nejad is a founding chair of the AAAI International Workshop on Health Intelligence and the lead editor of multiple book volumes on the applications of AI in healthcare and medicine. Dr. Martin Michalowski is a Foundation Research Professor in the School of Nursing at the University of Minnesota, where he co-directs the Center for Nursing Informatics and the Digital Health Lab. With a PhD in Computer Science from the University of Southern California, he applies advanced AI techniques, ranging from heuristic planning to large language models, in nursing informatics and personalized medicine. He co-leads the Nursing and AI Leadership Collaborative and the Mobile Emergency Triage (MET) research group, and has been recognized as a Fellow of the American Medical Informatics Association and the International Academy of Health Sciences Informatics. With more than 100 publications and as a founding chair of the International Workshop on Health Intelligence and co-chair of the AIME society, Dr. Michalowski has helped shape global dialogue on digital health innovation. His work is funded by NIH, NSF, DARPA, and DoD, and has led to award-winning papers and startup ventures. Dr. Simone Bianco is Vice President of Computation at Altos Labs, Bay Area Institute of Science, where he leads interdisciplinary research bridging biology, computational science, and regenerative medicine. Previously, he led synthetic biology and vaccine discovery efforts at IBM Research Almaden, contributing to multiple patents in systems biology and AI. Trained as a physicist, Dr. Bianco earned his degree from the University of Pisa and his PhD from the University of North Texas. His academic journey includes faculty positions at the College of William and Mary and UCSF, and he is a founding PI of the NSF Center for Cellular Construction. A TED speaker with over one million views, he actively promotes inclusive education and serves on the board of the PINC program at San Francisco State University. Dr. Bianco is also a co-chair of the AAAI International Workshop on Health Intelligence.

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