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The Ethical Governance of Artificial Intelligence and Machine Learning in Healthcare
This book explores the ethical governance of Artificial Intelligence (AI) & Machine Learning (ML) in healthcare. AI/ML usage in healthcare as well as our daily lives is not new. However, the direct, and oftentimes long-term effects of current technologies, in addition to the onset of future innovations, have caused much debate about the safety of AI/ML. On the one hand, AI/ML has the potential to provide effective and efficient care to patients, and this sways the argument in favor of continuing to use AI/ML; but on the other hand, the dangers (including unforeseen future consequences of the further development of the technology) leads to vehement disagreement with further AI/ML usage. Due to its potential for beneficial outcomes, the book opts to push for ethical AI/ML to be developed and examines various areas in healthcare, such as big data analytics and clinical decision-making, to uncover and discuss the importance of developing ethical governance for AI/ML in this setting.
Artificial Intelligence in Medicine
This book constitutes the refereed proceedings of the 13th Conference on Artificial Intelligence in Medicine, AIME 2011, held in Bled, Slovenia, in July 2011. The 42 revised full and short papers presented together with 2 invited talks were carefully reviewed and selected from 113 submissions. The papers are organized in topical sections on knowledge-based systems; data mining; special session on AI applications; probabilistic modeling and reasoning; terminologies and ontologies; temporal reasoning and temporal data mining; therapy planning, scheduling and guideline-based care; and natural language processing.
Nursing and Informatics for the 21st Century - Embracing a Digital World, 3rd Edition, Book 3
Innovation, Technology, and Applied Informatics for Nurses explores informatics trends emerging over the next decade including personalized healthcare, telehealth, artificial intelligence, voice recognition, and predictive analytics. Emphasis is placed on their importance, benefits, and key challenges for nurses. Digital health and patient-generated data in the context of remote monitoring are highlighted with a focus on digital health tools, issues, challenges, and implications for the future. A featured case study includes the use of patient-generated data during the COVID-19 pandemic including critical lessons learned. A discussion of the technological building blocks of sensors and the I...
Artificial Intelligence in Medicine
This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.
Bridging Artificial and Human Intelligence
This book reveals how human and artificial intelligence (AI) can be blended to augment the capacities of healthcare professionals, thereby enabling them to design their clinical work more effectively and efficiently. It provides a comprehensive overview about where human intelligence and AI overlap and differ, and how they can mutually enhance healthcare outcomes. Case studies illustrate the added value of AI for healthcare providers, patients and caregivers, and provides organizational strategies for implementing change and facilitating usability. It represents a valuable resource, providing insights into implementation strategies, as well as the ethical and legal frameworks relevant to AI ...
Knowledge Representation for Health Care
This book constitutes the refereed proceedings of the 6th International Workshop on Knowledge Representation for Health Care, KR4HC 2014, held as part of the Vienna Summer of Logic, VSL 2014, in Vienna, Austria, in July 2014. The workshop aimed at attracting the interest of novel research and advances contributing in the definition, representation and exploitation of health care knowledge in medical informatics. The 12 revised full research papers and 4 short papers presented in this book were carefully reviewed and selected from 26 submissions.
Artificial Intelligence in Medicine
This two-volume set LNAI 14844-14845 constitutes the refereed proceedings of the 22nd International Conference on Artificial Intelligence in Medicine, AIME 2024, held in Salt Lake City, UT, USA, during July 9-12, 2024. The 54 full papers and 22 short papers presented in the book were carefully reviewed and selected from 335 submissions. The papers are grouped in the following topical sections: Part I: Predictive modelling and disease risk prediction; natural language processing; bioinformatics and omics; and wearable devices, sensors, and robotics. Part II: Medical imaging analysis; data integration and multimodal analysis; and explainable AI.
Design Thinking Research
Extensive research conducted by the Hasso Plattner Design Thinking Research Program at Stanford University in Palo Alto, California, USA, and the Hasso Plattner Institute in Potsdam, Germany, has yielded valuable insights on why and how design thinking works. The participating researchers have identified metrics, developed models, and conducted studies, which are featured in this book, and in the previous volumes of this series. This volume provides readers with tools to bridge the gap between research and practice in design thinking with varied real world examples. Several different approaches to design thinking are presented in this volume. Acquired frameworks are leveraged to understand d...
