Nilmini Wickramasinghe is the inaugural Optus Chair and Professor of Digital Health at La Trobe University. She is also an inaugural member of the Australian Centre for AI in Medical Innovation. She has held or holds honorary research professor positions at Epworth HealthCare, the Peter MacCallum Cancer Centre, MCRI and Northern Health in Australia and the Cleveland Clinic in the US. After completing 5 degrees at the University of Melbourne, she was awarded a full scholarship to complete PhD studies at Case Western Reserve University, Cleveland, OH, USA and later was sponsored to complete executive education at Harvard Business School, Harvard University, Cambridge, MA, USA in Value-based HealthCare. For over 20 years, Professor Wickramasinghe has been actively researching and teaching within the health informatics/digital health domain in the US, Germany and Australia with a particular focus on designing, developing and deploying suitable models, strategies and techniques grounded in various management principles to facilitate the implementation and adoption of technology solutions to effect superior, value-based patient centric care delivery. Professor Wickramasinghe collaborates with leading scholars at various premier healthcare organisations and universities throughout Australasia, US and Europe and is well published, with more than 400 referred scholarly articles, more than 25 books, numerous book chapters, an encyclopaedia and a well-established funded research track record securing over $25M in funding from grants in US, Australia, Germany and China as a chief investigator. She holds a patent around analytics solution for managing healthcare data and a trademark. She is the editor-in-chief of Intl. J Networking and virtual Organisations( ) as well as the editor of the Springer book series Healthcare Delivery in the Information Age and the CRC Routledge book series on Analytics and AI in Healthcare. In 2020 she was awarded the prestigious Alexander von Humboldt life time award for outstanding contribution to Digital Health, the first time this honour has been bestowed to someone in the discipline of Digital Health worldwide.
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Paperback. Etat : new. Paperback. Responsible analytics in healthcare achieves superior health quality outcomes by ensuring data-driven decisions are ethical, transparent, and patient-centered. As healthcare systems rely on big data, AI, and predictive modeling, the importance of responsible data governance, bias mitigation, and privacy protection has become critical. Responsible analytics involves accountability in data collection, interpretation, and application in clinical and operational decisions. By promoting ethical standards and consumer trust, responsible analytics supports more equitable care delivery, enhances population health strategies, and drives improvements in patient outcomes. Responsible Analytics for Superior Health Quality Outcomes explores the potential for AI analytics to enable quality clinical decision making that leads to high quality and high value healthcare outcomes. It examines current techniques using AI tools, describing how best to harness their potential to ensure the delivery of quality healthcare. This book covers topics such as mental health, machine learning, and medical detection, and is a useful resource for business owners, medical professionals, healthcare workers, academicians, researchers, and data scientists. "This book aims to capture leading advances in AI, ML, and analytics, highlighting their strengths and weaknesses, as well as the opportunities and threats they present for superior healthcare delivery"-- Provided by publisher. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798337325460
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Responsible analytics in healthcare achieves superior health quality outcomes by ensuring data-driven decisions are ethical, transparent, and patient-centered. As healthcare systems rely on big data, AI, and predictive modeling, the importance of responsible data governance, bias mitigation, and privacy protection has become critical. Responsible analytics involves accountability in data collection, interpretation, and application in clinical and operational decisions. By promoting ethical standards and consumer trust, responsible analytics supports more equitable care delivery, enhances population health strategies, and drives improvements in patient outcomes. Responsible Analytics for Superior Health Quality Outcomes explores the potential for AI analytics to enable quality clinical decision making that leads to high quality and high value healthcare outcomes. It examines current techniques using AI tools, describing how best to harness their potential to ensure the delivery of quality healthcare. This book covers topics such as mental health, machine learning, and medical detection, and is a useful resource for business owners, medical professionals, healthcare workers, academicians, researchers, and data scientists. N° de réf. du vendeur 9798337325460
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Taschenbuch. Etat : Neu. Responsible Analytics for Superior Health Quality Outcomes | Nilmini Wickramasinghe (u. a.) | Taschenbuch | Englisch | 2025 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337325460 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 134421478
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