C5K - Leading Academic Research Publication

First Publish: 21-02-2025

Print ISBN: 978-1-967642-17-5

Dimensions: 22.9 cm x 15.2 cm x 2.5 cm

Item Weight: 250 gm

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Rapid advancements in artificial intelligence (AI) are ushering in a transformational era for the healthcare sector. The practice, delivery, and experience of medicine are being transformed by what was formerly the purview of science fiction. AI is no longer an add-on to healthcare; rather, it is becoming a crucial component of its advancement, from optimizing administrative processes to directing robotic procedures, from real-time patient monitoring to highly customized treatment regimens based on genetic information. Medicine is a complicated, data-rich, and decision-intensive field by nature. Because of this, it is ideally equipped to take advantage of AI's processing capacity and pattern recognition abilities. The amount of data generated by wearable technology, pathology slides, genetic sequences, medical imaging, electronic health records, and even doctors' notes is too great for a single person to handle. With previously unheard-of speed and depth, AI technologies can mine this data to find insights, make predictions, and support decisions with ever-increasing accuracy. These skills are changing the standard of care, not merely improving the way healthcare is delivered. The promise of AI in medicine to close gaps in quality and access is among its most exciting features. AI-enabled diagnostic technologies can help frontline healthcare workers in low-resource environments by providing clinical decision assistance even when specialists are not available. Early treatments are made possible by predictive analytics, which can assist prevent issues before they worsen. A more fair, proactive, and patient-centered healthcare future is being heralded by the expansion of access to high-quality care to rural populations through AI-enabled telemedicine, remote monitoring, and mobile diagnostics. This change is not without difficulties, though. Technical, ethical, and regulatory issues become more prominent when AI is incorporated into medical practice. Transparency, algorithmic bias, and data privacy issues need to be rigorously addressed. Furthermore, it will be crucial to preserve confidence between patients, providers, and intelligent systems as AI grows more independent. Enhancing human judgment rather than replacing it should be the aim; AI should be used to support clinicians rather than to replace them.

AI in Medicine: Transforming Diagnosis, Treatment, and Care is a comprehensive exploration of how artificial intelligence is redefining every dimension of modern health care. With rapid advancements in machine learning, natural language processing, computer vision, and robotics, AI has moved beyond theoretical research and is now driving real-world applications that are revolutionizing the way health care is delivered, managed, and experienced. This book provides an in-depth analysis of the critical areas where AI is making a transformative impact. It examines how intelligent algorithms are improving diagnostic accuracy by detecting patterns in medical imaging, pathology reports, and genomic data that often escape human observation. It further highlights the role of AI in enhancing treatment planning, supporting precision medicine, and enabling personalized care tailored to individual patients’ needs. Beyond clinical settings, the book delves into the integration of AI in hospital management systems, electronic health records, telemedicine, wearable devices, and remote monitoring solutions. These innovations not only improve efficiency and reduce costs but also expand access to quality health care in underserved regions, bridging the gap between patients and medical professionals worldwide. At the same time, the book does not overlook the ethical, social, and regulatory challenges posed by AI adoption. Issues of patient privacy, data security, algorithmic bias, transparency, and accountability are critically discussed, providing readers with a balanced perspective on the benefits and risks associated with AI-driven health care. By addressing these challenges, the book emphasizes the need for responsible innovation and collaborative frameworks among health professionals, policymakers, technologists, and researchers. Written in an accessible yet scholarly style, this book is intended for a diverse audience that includes medical practitioners, health care administrators, researchers, engineers, policymakers, and students. Whether you are a health professional seeking to integrate AI into practice, a researcher aiming to explore cutting-edge applications, or a reader interested in the future of medicine, this book offers valuable insights and practical knowledge. Ultimately, AI in Medicine: Transforming Diagnosis, Treatment, and Care serves as both a guide and a visionary outlook on the future of health care. It presents not just the current landscape of AI technologies but also forward-looking perspectives on how innovation will continue to evolve, shaping a more efficient, accessible, and patient-centered health care system in the years ahead.

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