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Gesamtkatalog

Catalogue complet

Internet of Medical Things

Case Studies and Applications in Healthcare

<ol> <li>Introduction to IoMT: A Revolution in Healthcare 2. Optimizing Smart Hospitals with IoMT: A Deep Dive into the Next-Generation Paradigm for Digital Healthcare 3. Internet of Medical Things: Architecture and Technologies 4. Tapestry of Promise and Peril: NLP, AI, and IoMT in Healthcare Transformation - A Review 5. AI - Driven Health Coach for Diabetes Management 6. An Enhancement of Security System using Curve Based Cryptosystem with Decentralized Scalable Group Key Agreement for IoMT 7. Post Processing of Unmanned Aerial Vehicle Images of Search &amp; Rescue Mission 8. Revolutionizing Mental Health Care: The Transformative Power of Internet of Medical Things (IoMT): A Comprehensive Overview and Case Studies 9. Internet of Medical Things Based Smart System for the Mental Healthcare Challenges in 21st Century: Trends and Progress 10. Healing Beyond Beliefs: A PostHumanist Reading of IoMT Advancements 11. Adverse Childhood Experiences, Psychological Well-Being and Grit: A Comparative Study Between LGBTQIA+ And Cis-Heterogenous Sample of India 12. Global research trends on implementing internet based mental health programs: A bibliometric analysis 13. Transformative Tales: Unveiling Success Stories and Advancements in Healthcare through Internet of Medical Things (IoMT) and Machine Learning Integration</li> </ol>

How the thoughtful reimagining of health-centric built environments both locally and globally can better serve vulnerable populations and reduce health disparities in a climate-threatened world.As climate change accelerates, its impact on public health grows, disproportionately affecting medically underserved populations. In Architecture and Health Equity in an Imperiled World, Stephen Verderber addresses the urgent need for innovative architectural and ecologically responsible strategies to confront health inequities exacerbated by the global climate crisis. This book highlights the critical role of health-centric architecture in mitigating these inequities and creating resilient, therapeutically supportive environments. Combining insights from public health, architecture, and climate science, this book examines how the built environment can both contribute to and alleviate health disparities. Chapters examine the unique vulnerabilities of health-focused built environments including hospitals, outpatient clinics, and long-term care facilities amid the devastating effects of rising sea levels, extreme weather events, and escalating public health emergencies. Emphasizing the urgent need for innovative, resilient design strategies, Architecture and Health Equity in an Imperiled World illustrates how thoughtful and compassionate design innovations can better serve increasingly vulnerable populations both locally and globally. An essential resource for health care leaders, architects, and policymakers, Architecture and Health Equity in an Imperiled World challenges traditional, increasingly obsolete policies and protocols, advocating instead for innovative strategies and solutions to improve health and promote sustainability. This book offers a bold new vision for leveraging architectural design and its diverse benefits to society to ensure that communities can thrive sustainably and regeneratively in an uncertain future.

Architecture and Health Equity in an Imperiled World

Data-Driven Modeling

How statistical invariances will help us build AI systems exhibiting human-like performance by following human-like strategies. Current machine learning systems crumble when the distributions of training and testing examples differ in spurious correlations. This is a major roadblock toward the development of advanced machine intelligence, which demands not only human-like performance but the deployment of human-like strategies. The prevalent approach in AI, fixated on recklessly minimizing average training error, falls short in producing AI systems capable of authentic out-of-distribution generalization. This book introduces the Invariance Principle, a new epistemological tool to unearth correlations invariant across diverse collections of empirical data. The Invariance Principle, encapsulated in the axiom “frame your problem so its answer matches across circumstances," will not only find its practical incarnation in the family of Invariant Risk Minimization algorithms, but also illuminate our understanding of causation. It will permeate topics such as environment discovery, large-language models, self-supervised learning, mixing data augmentation, uncertainty estimation, and fairness. The author argues that the Invariance Principle is a central inductive bias fueling advances across fields of knowledge, such as physics, metaphysics, and cognitive science. The final chapter includes personal examples of how invariance has shaped the author’s understanding of his own subjective experience, as well as how he has interpreted both Eastern and Western philosophical traditions.

The Invariance Principle

Resistance in the Age of Artificial Intelligence

Algorithmic Capital

Augmented and Virtual Reality in Healthcare

Distributed and Parallel Computing

Advances in Industrial and Systems Engineering

Advances in Human-AI Collaboration

The Lies We’ve Been Sold and the Policies That Can Save Us

How Not to Die (Too Soon)

Powered by Hyperscale Computing and Next Generation Networks

AI-Driven Smart Healthcare

Methods, Applications, and Implications

Adaptive AI in Sensor Informatics

Practical Risk Management Using Real-World Incidents

The Nist 2.0 Cybersecurity Framework

The MIT Press Essential Knowledge series

How tech companies, journalists, and policymakers can prevent AI decision-making from going wrong. Our lives are increasingly governed by automated systems influencing everything from medical care to policing to employment opportunities, but researchers and investigative journalists have proven that AI systems regularly get things wrong. Auditing AI is a first-of-its-kind exploration of why and how to audit artificial intelligence systems. It offers a simple roadmap for using AI audits to make product and policy changes that benefit companies and the public alike. The book aims to convince readers that AI systems should be subject to robust audits to protect all of us from the dangers of these systems. Readers will come away with an understanding of what an AI audit is, why AI audits are important, key components of an audit that follows best practices, how to interpret an audit, and the available choices to act on an audit’s results. The book is organized around canonical examples: from AI-powered drones mistakenly targeting civilians in conflict areas to false arrests triggered by facial recognition systems that misidentified people with dark skin tones to HR hiring software that prefers men. It explains these definitive cases of AI decision-making gone wrong and then highlights specific audits that have led to concrete changes in government policy and corporate practice. The Marquand House Collective: Marc Aidinoff, Lena Armstrong, Esha Bhandari, Ellery Roberts Biddle, Motahhare Eslami, Karrie Karahalios, Nate Matias, Danaé Metaxa, Alondra Nelson, Christian Sandvig, and Kristen Vaccaro.

Auditing AI

Internet of Medical Things

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