
Dimensions of Intelligent Analytics for Smart Digital Health Solutions
Description
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This book shows how the tools, techniques, technologies, and tactics around analytics and AI can be best leveraged and utilised to realise a healthcare value proposition of better quality, better access and high value for everyone every day, everywhere. The book presents a triumvirate approach including technical, business and medical aspects of data and analytics and by so doing takes a responsible approach to this key area.
This work serves to introduce the critical issues in AI and analytics for healthcare to students, practitioners, and researchers.
Reviews / Votes
"I have had the pleasure of being a contributing author to one of Professor Wickramasinghe's previous books on digital health. Once again, she and her co-editors have assembled a roster of domain experts that cover currently relevant topics in the rapidly changing field of digital health. I appreciate how this book weaves in the areas of technical, management, clinical, and human factor considerations into the delivery of healthcare today. As a practicing clinician, I understand how analytic and AI technologies will play an increasingly critical role in effecting value-based care outcomes that are more precise and bespoke to the individual patient. I recommend this book as a critical read to all stakeholders who seek a greater understanding of just how technology plays an increasingly pertinent role in the delivery of care now and into the future."Duane F. Wisk, DO, MPH, FACOEM, Managing Partner, GlobalMed Physicians
"AI is the tool that promises to change everything-with good reason. But without the intelligent analytics discussed in this groundbreaking book, it could just be the source of confusion and error. The two dimensions are critical to realizing its promise."
Albert J. Weatherhead III, Professorship of Management, Dean and Professor, Department of Banking and Finance, Weatherhead School of Management, USA
"Using data driven approaches in providing highly reliable patient care is the right thing to do. As technologies have advanced, Wickramasinghe et al. provide a glimpse into the management, technical, clinical and human factors associated with the critically important topics of applying analytics, artificial intelligence and machine learning to healthcare. Developing patient centered and clinician derived approaches to improving care models using descriptive, diagnostic, predictive and prescriptive analytics is the right approach, and the authors are expertly leading the readers to expedite their journey to improving healthcare."
Jonathan Schaffer, MD, MBA, Managing Director, eCleveland Clinic, Information Technology Division of Cleveland Clinic, USA
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Persons
Freimut Bodendorf earned a degree in computer science at the School of Engineering, University of Erlangen-Nuremberg. He also earned a PhD in information systems. Subsequently, he was head of an IS Department at the University Hospital and Medical School at the University of Freiburg, Germany; professor at the Postgraduate School of Engineering in Nuremberg, Germany; and head of the Department of Computer Science and Information Systems at the University of Fribourg, Switzerland. He also is the head of the research group Management Intelligence Systems of the Institute of Information Systems at the University of Erlangen-Nuremberg. He is a faculty member of the School of Business and Economics as well as the School of Engineering and the School of Natural Sciences. Recently he was appointed to be a Research Fellow of the Fraunhofer Institute IIS, the largest institute in Germany. His scienti?c work focuses on business intelligence and digital health, including advanced data analytics, responsible arti?cial intelligence, intelligent assistance, data sharing and federated learning ecosystems. His research projects investigate and create solutions in the ?elds of digital transformation in healthcare and digital support of individual wellness.
Mathias Kraus is an Assistant Professor for Data Analytics at the Institute for Information Systems, FAU Erlangen-Nuernberg, where he also heads the White-Box AI research group. Prior to this appointment, he was a research assistant at ETH Zurich and the University of Freiburg. In his current role, he develops advances in data analytics with a focus on transparency and reliability in machine learning models. He has made several contributions to the scienti?c community through his work, which has been published in leading information systems and operations research journals and at prestigious computer science conferences.
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