Preventive Healthcare Ai And Data Analytics Transforming Insurance Through Proactive Care And Predictive Insights 2025
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Preventive Healthcare Ai And Data Analytics Transforming Insurance Through Proactive Care And Predictive Insights 2025
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Author : Ruchi Mangharamani, Dr. Gaurav Pandey
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Preventive Healthcare Ai And Data Analytics Transforming Insurance Through Proactive Care And Predictive Insights 2025 written by Ruchi Mangharamani, Dr. Gaurav Pandey and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In recent years, the convergence of preventive healthcare, artificial intelligence (AI), and data analytics has sparked a revolution in the insurance industry. Traditionally, insurance models have focused on risk assessment and mitigation, often relying on reactive strategies to manage the health of policyholders. However, with the growing capabilities of AI and data analytics, a new era of proactive care is emerging—one that shifts the focus from merely compensating for health-related risks to actively preventing them before they manifest. This transformation is not only reshaping how insurance companies approach underwriting, claims, and pricing but also influencing the broader healthcare landscape. By leveraging AI’s predictive capabilities and data analytics, insurers are gaining the ability to identify early signs of health issues, thereby enabling proactive interventions. These insights empower both insurers and policyholders to make informed decisions that improve long-term health outcomes, reduce costs, and optimize care delivery. As the healthcare system transitions towards a more holistic, data-driven model, this book explores how preventive healthcare, underpinned by cutting-edge technology, is revolutionizing the insurance industry. We will examine the integration of AI and data analytics into insurance strategies, highlight the innovative ways these tools are driving preventive care, and consider the potential for predictive insights to reshape the future of healthcare insurance. In the chapters ahead, we will delve into the practical applications of these technologies, discuss the ethical and privacy implications, and explore the potential benefits for both insurers and consumers. The goal is to provide a comprehensive understanding of how this evolving landscape is not just improving the efficiency of insurance practices, but also fostering a culture of health optimization, resulting in a win-win scenario for all stakeholders involved. The journey towards a more intelligent, predictive, and preventive insurance ecosystem has only just begun, and it holds the promise of a healthier, more sustainable future for individuals and communities worldwide. Authors
15 Entrepreneurship Trends For 2025
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Author : Jon S. Wilson
language : en
Publisher: Divya Agarwal
Release Date : 2025-04-26
15 Entrepreneurship Trends For 2025 written by Jon S. Wilson and has been published by Divya Agarwal this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-26 with Business & Economics categories.
The book Entrepreneurship Trends for 2025 is a comprehensive guide for aspiring business leaders and innovators seeking to thrive in the fast-evolving landscape of modern entrepreneurship. Drawing from cutting-edge trends, this book explores the latest advancements in technology, business strategy, and consumer behavior, offering invaluable insights on how to navigate and capitalize on the opportunities of the future. Written by an expert in the field, it provides actionable advice, real-world examples, and practical frameworks to help entrepreneurs launch and scale successful ventures. Whether you are starting your first business or scaling an existing one, this book equips you with the knowledge and tools necessary to stay ahead in a rapidly changing world.
The Transformative Power Of Ai Applications In Healthcare
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Author : Ayman Elmassarawy
language : en
Publisher: Ayman Elmassarawy
Release Date : 2025-01-24
The Transformative Power Of Ai Applications In Healthcare written by Ayman Elmassarawy and has been published by Ayman Elmassarawy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-24 with Computers categories.
Artificial intelligence (AI) is revolutionizing the healthcare industry, reshaping how medicine is practiced and how care is delivered. The Transformative Power of AI Applications in Healthcare delves into the dynamic intersection of AI and medicine, offering readers a profound understanding of the innovations driving change and the challenges that accompany them. With its compelling blend of technological insight and real-world applications, this book serves as an essential resource for medical professionals, technologists, policymakers, and curious minds. Key Themes and Innovations The book begins by laying the foundational concepts of AI in healthcare, tracing its evolution from early data visualization techniques to today’s advanced machine learning algorithms. Readers are introduced to the transformative potential of predictive analytics, where wearable devices, early warning systems, and disease modeling enable the detection and prevention of illnesses long before symptoms manifest. Revolutionizing Diagnostics: One of the standout themes is AI’s role in enhancing diagnostic accuracy and efficiency. Chapters illustrate how deep learning algorithms, such as those used in radiology and pathology, are empowering clinicians with faster, more reliable diagnoses. Case studies, including AI’s application in detecting diabetic retinopathy and breast cancer, reveal its ability to expand diagnostic capabilities, particularly in underserved regions. Personalized Medicine and Genomics: The exploration of genomics and pharmacogenomics highlights how AI is personalizing care to unprecedented levels. The book unpacks the shift from generic treatment protocols to precision therapies tailored to individual genetic profiles, citing examples like targeted cancer treatments and optimized drug dosing strategies. Surgical Innovations and Robotics: AI’s integration into robotic surgery systems is revolutionizing operating rooms worldwide. From minimally invasive procedures to real-time decision-making tools, readers learn how AI enhances surgical precision, reduces risks, and expands access to complex surgeries. The potential for remote surgeries and autonomous systems is also explored, showcasing the far-reaching impact of this technology. Public Health and Crisis Management: The role of AI in addressing global health crises takes center stage, with detailed discussions on how platforms like BlueDot and HealthMap provided early warnings during the COVID-19 pandemic. The book also examines AI’s contributions to vaccine development, resource allocation, and public health strategies, highlighting its transformative role in safeguarding global populations. Ethical Considerations and Challenges The book does not shy away from critical discussions on the ethical implications of AI. Topics such as algorithmic bias, data privacy, and equitable access to AI-driven innovations are examined with rigor. Readers are invited to consider how these challenges can be addressed through transparent, inclusive practices that prioritize fairness and human welfare. Vision for the Future Looking ahead, the book speculates on emerging frontiers of AI in healthcare. From mental health applications and autonomous diagnostics to advancements in bioprinting and chronic disease management, the potential for future breakthroughs is boundless. The narrative challenges readers to envision a healthcare system where AI seamlessly integrates with human expertise to deliver smarter, more compassionate care. Why This Book Matters At its core, The Transformative Power of AI Applications in Healthcare is not just about technology—it’s about the human impact. By offering an in-depth look at the advancements and ethical dilemmas surrounding AI, the book equips readers with the knowledge and inspiration to participate in shaping the future of medicine. It is both a roadmap and a call to action, urging readers to engage with the transformative power of AI and to champion its responsible implementation. This book is an indispensable guide for anyone interested in understanding how AI is reshaping healthcare. It illuminates the path forward, bridging the gap between innovation and humanity, and fostering a vision of a healthcare system that is smarter, more equitable, and profoundly impactful.
Artificial Intelligence In Healthcare
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Author : Adam Bohr
language : en
Publisher: Academic Press
Release Date : 2020-06-21
Artificial Intelligence In Healthcare written by Adam Bohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-21 with Computers categories.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Computational Intelligence In Machine Learning
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2025-08-02
Computational Intelligence In Machine Learning written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-02 with Computers categories.
This book features selected proceedings from the International Conference on Computational Intelligence in Machine Learning (ICCIML 2023). It covers the latest research trends and developments in various fields, including machine learning, smart cities, the Internet of Things (IoT), artificial intelligence, cyber-physical systems, cybernetics, data science, neural networks, and cognition, among others. The book also emphasizes the comprehensive nature of computational intelligence, artificial intelligence, machine learning, and deep learning by highlighting their roles in modeling, identification, optimization, prediction, forecasting, and controlling future intelligent systems. This volume serves as a valuable resource for researchers in both academia and industry, offering in-depth insights from fundamental research contributions. It focuses on methodological and application perspectives, enhancing the understanding of AI and ML approaches and their capabilities in addressing a diverse range of problems across various industries and real-world applications.
Integrating Technology In Physiotherapy From Virtual Rehab To Wearable Devices
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Author : Dr. Shivanee M. Kaul
language : en
Publisher: Chyren Publication
Release Date : 2025-06-30
Integrating Technology In Physiotherapy From Virtual Rehab To Wearable Devices written by Dr. Shivanee M. Kaul and has been published by Chyren Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Antiques & Collectibles categories.
Machine Learning In Insurance
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Author : Jens Perch Nielsen
language : en
Publisher: MDPI
Release Date : 2020-12-02
Machine Learning In Insurance written by Jens Perch Nielsen and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-02 with Business & Economics categories.
Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries’ “preferred methods” were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure.
Competing On Analytics
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Author : Thomas H. Davenport
language : en
Publisher: Harvard Business Press
Release Date : 2007-03-06
Competing On Analytics written by Thomas H. Davenport and has been published by Harvard Business Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-06 with Business & Economics categories.
You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics.
Artificial Intelligence
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Author : Sandeep Reddy
language : en
Publisher: CRC Press
Release Date : 2020-12-02
Artificial Intelligence written by Sandeep Reddy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-02 with Business & Economics categories.
The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to an increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and health authorities have prioritized the application of AI in the delivery of healthcare. Also, technological giants and leading universities have established teams dedicated to the application of AI in medicine. These trends will mean an expanded role for AI in the provision of healthcare. Yet, there is an incomplete understanding of what AI is and its potential for use in healthcare. This book discusses the different types of AI applicable to healthcare and their application in medicine, population health, genomics, healthcare administration, and delivery. Readers, especially healthcare professionals and managers, will find the book useful to understand the different types of AI and how they are relevant to healthcare delivery. The book provides examples of AI being applied in medicine, population health, genomics, healthcare administration, and delivery and how they can commence applying AI in their health services. Researchers and technology professionals will also find the book useful to note current trends in the application of AI in healthcare and initiate their own projects to enable the application of AI in healthcare/medical domains.
Big Data At Work
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Author : Thomas Davenport
language : en
Publisher: Harvard Business Review Press
Release Date : 2014-02-04
Big Data At Work written by Thomas Davenport and has been published by Harvard Business Review Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-04 with Business & Economics categories.
Go ahead, be skeptical about big data. The author was—at first. When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold. This book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or develop the kinds of people who make big data work • The key success factors in implementing any big data project • How big data is leading to a new approach to managing analytics With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.