Generative Ai In Healthcare

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Artificial Intelligence in Healthcare

Author : Adam Bohr
Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Generative AI for Healthcare

Author : Rakesh Kumar
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (228 download)

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Book Synopsis Generative AI for Healthcare by : Rakesh Kumar

Download or read book Generative AI for Healthcare written by Rakesh Kumar and published by Independently Published. This book was released on 2024-04-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, generative artificial intelligence (AI) has emerged as a powerful tool with transformative potential across various industries, including healthcare. The convergence of advanced machine learning techniques, abundant healthcare data, and innovative algorithms has paved the way for generative AI to revolutionize medical research, diagnosis, treatment, and patient care. "Generative AI for Healthcare" is a comprehensive guide that explores the intersection of generative AI and healthcare, providing insights into the latest developments, applications, challenges, and future directions in this rapidly evolving field. From synthesizing medical images and generating electronic health records to personalized medicine and drug discovery, this book delves into the diverse ways in which generative AI is reshaping the landscape of healthcare delivery and biomedical research. Drawing upon expertise from interdisciplinary domains such as computer science, medicine, bioinformatics, and data science, "Generative AI for Healthcare" offers a holistic perspective on the potential and pitfalls of leveraging generative AI in healthcare. Through real-world case studies, practical examples, and expert insights, readers will gain a deeper understanding of how generative AI technologies are being applied to address critical healthcare challenges, improve patient outcomes, and accelerate medical innovation. Whether you are a healthcare professional, researcher, data scientist, or AI enthusiast, this book serves as a valuable resource for navigating the complex intersection of generative AI and healthcare. By exploring cutting-edge techniques, emerging trends, and ethical considerations, "Generative AI for Healthcare" empowers readers to harness the power of generative AI to drive positive change and innovation in healthcare delivery, ultimately advancing the future of medicine and improving human health worldwide.

Machine Learning and AI for Healthcare

Author : Arjun Panesar
Publisher : Apress
ISBN 13 : 1484237994
Total Pages : 390 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Machine Learning and AI for Healthcare by : Arjun Panesar

Download or read book Machine Learning and AI for Healthcare written by Arjun Panesar and published by Apress. This book was released on 2019-02-04 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.

Llms and Generative AI for Healthcare

Author : Kerrie Holley
Publisher :
ISBN 13 : 9781098160920
Total Pages : 0 pages
Book Rating : 4.1/5 (69 download)

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Book Synopsis Llms and Generative AI for Healthcare by : Kerrie Holley

Download or read book Llms and Generative AI for Healthcare written by Kerrie Holley and published by . This book was released on 2024-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare. Authors Kerrie Holley and Manish Mathur from Google's Healthcare and Life Sciences Industry team help you explore real-world applications of these technologies in healthcare, from personalized patient care and drug discovery to enhanced medical imaging and robot-assisted surgeries. You'll also learn the challenges of using these technologies--and the ethical implications of their application in this field. With this book, you will: Learn how LLMs and generative AI can help address and transform healthcare issues Explore the basics of LLMs and generative AI and learn how they work Learn how these technologies are being applied in healthcare today Understand several LLM and generative AI use cases Examine the ethics and challenges of applying LLMs and generative AI to healthcare Understand the potential use of LLMs and generative AI in healthcare in the near term and their prospects for the future

Generative AI in Healthcare

Author : Anand Vemula
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (29 download)

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Book Synopsis Generative AI in Healthcare by : Anand Vemula

Download or read book Generative AI in Healthcare written by Anand Vemula and published by Independently Published. This book was released on 2024-06-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI in Healthcare: A Comprehensive Guide" explores the transformative role of artificial intelligence (AI) in revolutionizing healthcare practices. This book serves as a comprehensive resource for healthcare professionals, technologists, and enthusiasts interested in understanding how generative AI is reshaping the future of medicine. The book begins with an exploration of the foundational concepts of generative AI, providing insights into neural networks, deep learning fundamentals, and various generative models such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformer models. It delves into the importance of high-quality data and robust infrastructure necessary to support AI applications in healthcare settings. Part II of the book focuses on practical applications of generative AI in healthcare, including enhancing medical imaging accuracy, accelerating drug discovery processes, and personalizing treatment plans based on individual patient data. Real-world case studies and examples illustrate how AI is automating tasks, improving diagnostic accuracy, and supporting clinical decision-making. In Part III, the book addresses implementation challenges such as technical integration into existing healthcare systems, change management strategies, and ethical considerations around data privacy and algorithmic bias. It emphasizes the importance of training healthcare professionals to effectively leverage AI tools while adhering to regulatory standards. Part IV explores future directions of generative AI in healthcare, discussing emerging technologies like AI-enabled IoT devices, quantum computing applications, and advanced AI models. Global perspectives highlight international collaborations and case studies from different countries, showcasing diverse approaches to integrating AI in healthcare. Concluding with a forward-looking perspective, the book discusses long-term predictions for AI's role in healthcare, emphasizing its potential to enhance preventive care, improve patient outcomes, and streamline healthcare delivery.

Machine Learning and Generative AI in Smart Healthcare

Author : Purushotham, Swarnalatha
Publisher : IGI Global
ISBN 13 :
Total Pages : 474 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Machine Learning and Generative AI in Smart Healthcare by : Purushotham, Swarnalatha

Download or read book Machine Learning and Generative AI in Smart Healthcare written by Purushotham, Swarnalatha and published by IGI Global. This book was released on 2024-08-28 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: The healthcare landscape is constantly evolving, and one of the most significant concerns that healthcare professionals deal with is understanding how to use biomedical intelligence to improve patient outcomes. With the increasing complexity of healthcare computing systems, including technologies like deep learning and the Internet of Things, it can be challenging to navigate these advancements. Machine Learning and Generative AI in Smart Healthcare is a practical tool for healthcare professionals, researchers, and policymakers who are seeking to implement biomedical intelligence solutions. It provides a clear roadmap for using prescriptive and predictive analytics in machine learning to enhance healthcare outcomes. Going beyond the basics, it delves into healthcare computing and networking complexities. By delving into topics such as data mining, disease prediction, and AI applications, deep learning approaches, decision support systems, and optimization techniques, this book equips readers with the practical knowledge they need to optimize healthcare delivery and management.

AI-First Healthcare

Author : Kerrie L. Holley
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492063126
Total Pages : 222 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis AI-First Healthcare by : Kerrie L. Holley

Download or read book AI-First Healthcare written by Kerrie L. Holley and published by "O'Reilly Media, Inc.". This book was released on 2021-04-19 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI is poised to transform every aspect of healthcare, including the way we manage personal health, from customer experience and clinical care to healthcare cost reductions. This practical book is one of the first to describe present and future use cases where AI can help solve pernicious healthcare problems. Kerrie Holley and Siupo Becker provide guidance to help informatics and healthcare leadership create AI strategy and implementation plans for healthcare. With this book, business stakeholders and practitioners will be able to build knowledge, a roadmap, and the confidence to support AIin their organizations—without getting into the weeds of algorithms or open source frameworks. Cowritten by an AI technologist and a medical doctor who leverages AI to solve healthcare’s most difficult challenges, this book covers: The myths and realities of AI, now and in the future Human-centered AI: what it is and how to make it possible Using various AI technologies to go beyond precision medicine How to deliver patient care using the IoT and ambient computing with AI How AI can help reduce waste in healthcare AI strategy and how to identify high-priority AI application

Generative AI in Healthcare

Author : Anand Vemula
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (274 download)

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Book Synopsis Generative AI in Healthcare by : Anand Vemula

Download or read book Generative AI in Healthcare written by Anand Vemula and published by Independently Published. This book was released on 2024-06-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Generative AI in Healthcare: Innovations and Applications" is an insightful exploration into the transformative power of generative artificial intelligence within the healthcare industry. This book delves into the cutting-edge applications of generative AI that are revolutionizing medical practices, enhancing diagnostic accuracy, and personalizing patient care. The book begins with an introduction to the fundamental concepts of generative AI, including an overview of machine learning, deep learning, and the specific models that drive generative AI, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). It establishes a strong foundation by explaining how these technologies work and their potential to generate new, high-quality data from existing datasets. In the subsequent chapters, the book presents a series of real-world applications and case studies. It highlights how generative AI is enhancing medical imaging by improving image quality and enabling automated image analysis. Through detailed examples, readers learn how AI-driven tools are assisting radiologists and pathologists in making more accurate diagnoses faster than ever before. The book also covers the impact of generative AI on drug discovery and development. It showcases how AI is accelerating the identification of drug candidates and optimizing clinical trials, thereby reducing the time and cost involved in bringing new medications to market. Personalized medicine is another key focus, demonstrating how AI tailors treatments to individual patients' genetic profiles and medical histories, leading to more effective and targeted therapies. Technical and ethical considerations are thoroughly addressed, ensuring a balanced discussion of the challenges and solutions associated with implementing generative AI in healthcare. Issues such as data quality, model accuracy, integration with existing systems, and the ethical implications of AI are examined, providing a comprehensive understanding of what it takes to deploy these technologies responsibly. Finally, the book looks to the future, predicting trends and emerging technologies that will continue to shape the landscape of healthcare. It offers practical advice for healthcare professionals, researchers, and policymakers on building and sustaining AI initiatives. "Generative AI in Healthcare: Innovations and Applications" is an essential read for anyone interested in the future of healthcare technology, providing a clear, accessible, and detailed guide to the exciting possibilities of generative A

Deep Medicine

Author : Eric Topol
Publisher : Basic Books
ISBN 13 : 1541644646
Total Pages : 373 pages
Book Rating : 4.5/5 (416 download)

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Book Synopsis Deep Medicine by : Eric Topol

Download or read book Deep Medicine written by Eric Topol and published by Basic Books. This book was released on 2019-03-12 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Artificial Intelligence in Medicine

Author : David Riaño
Publisher : Springer
ISBN 13 : 303021642X
Total Pages : 431 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Artificial Intelligence in Medicine by : David Riaño

Download or read book Artificial Intelligence in Medicine written by David Riaño and published by Springer. This book was released on 2019-06-19 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Intelligence in Healthcare

Author : Parag Mahajan
Publisher : Medmantra, LLC
ISBN 13 : 9781954612020
Total Pages : 628 pages
Book Rating : 4.6/5 (12 download)

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Book Synopsis Artificial Intelligence in Healthcare by : Parag Mahajan

Download or read book Artificial Intelligence in Healthcare written by Parag Mahajan and published by Medmantra, LLC. This book was released on 2021-02 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: ① Do you know what AI is doing to improve our health and wellbeing? ② Does this new technology concern you, or impress you? ③ Do you want to know more about the future of AI in healthcare? Technology continues to advance at a pace that can seem bewildering. Nowhere else is it moving faster than in the health sector, where ♥AI is now being used to improve millions of lives♥. In this book, ◆ Artificial Intelligence in Healthcare: AI, Machine Learning, and Deep and Intelligent Medicine Simplified for Everyone ◆, you can discover the great improvements that AI is making, with chapters covering: The current applications and future of AI in healthcare and all major medical specialties ✓ The benefits and risks weighed up ✓ The ethics involved ✓ Machine learning and data science simplified ✓ AI's role in medical research and education, health insurance, drug discovery, electronic health records, and the fight against COVID-19 ✓ The roles that major corporations and start-up companies are playing ✓ The implementation of AI in clinical practice ✓ And lots more... Quite simply the most authoritative text on the subject, Artificial Intelligence in Healthcare - 3rd Edition, is an absorbing and compelling read for anyone who wants to know more. It is packed with more updated information than any other book currently available, written in easy-to-understand language, and accessible to all.

LLM and Generative AI for Healthcare

Author : Anand Vemula
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (331 download)

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Book Synopsis LLM and Generative AI for Healthcare by : Anand Vemula

Download or read book LLM and Generative AI for Healthcare written by Anand Vemula and published by Independently Published. This book was released on 2024-07-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "LLM and Generative AI for Healthcare: A Comprehensive Guide" explores the transformative power of Large Language Models (LLMs) and Generative AI in the healthcare industry. This book provides a deep dive into how these cutting-edge technologies are revolutionizing medical practices, enhancing patient care, and optimizing operational efficiency. The journey begins with an introduction to LLMs and Generative AI, offering a clear understanding of their evolution, capabilities, and significance in healthcare. It delves into the fundamentals of healthcare data, emphasizing the types of data, privacy, security considerations, and regulatory compliance, which are crucial for any AI application in this sector. In the second part, the book showcases various applications of AI in healthcare. It covers AI's role in medical imaging and diagnostics, highlighting advancements in radiology and automated image analysis through real-world case studies. The book also explores Natural Language Processing (NLP) applications, including clinical documentation, EHR management, voice assistants, and text mining for research and drug discovery. Furthermore, it discusses personalized medicine, predictive analytics for patient outcomes, and AI's role in drug discovery and development. The third part focuses on the implementation of AI solutions in healthcare. It provides practical guidance on designing AI systems, integrating them with existing healthcare infrastructure, and key design considerations. The book also covers data management, preprocessing techniques, and ensuring data quality, followed by model training, evaluation, deployment strategies, and continuous improvement. Real-world case studies and lessons learned from successful AI implementations are presented in the fourth part. This section also addresses the ethical and legal considerations of AI in healthcare, emphasizing the importance of fairness, transparency, and compliance with regulations. The book concludes with a look at future trends and innovations in AI, preparing readers for upcoming technological advancements. The final part offers hands-on tutorials and exercises, guiding readers through the setup and use of popular AI tools and libraries. It includes basic and advanced projects, such as building medical chatbots and diagnostic tools, to reinforce learning and practical application. "LLM and Generative AI for Healthcare: A Comprehensive Guide" is an essential resource for healthcare professionals, data scientists, and AI enthusiasts looking to harness the power of AI to improve healthcare outcomes.

LLMs and Generative AI for Healthcare

Author : Kerrie Holley
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098160894
Total Pages : 222 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis LLMs and Generative AI for Healthcare by : Kerrie Holley

Download or read book LLMs and Generative AI for Healthcare written by Kerrie Holley and published by "O'Reilly Media, Inc.". This book was released on 2024-08-20 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare. Authors Kerrie Holley, former Google healthcare professionals, guide you through the transformative potential of large language models (LLMs) and generative AI in healthcare. From personalized patient care and clinical decision support to drug discovery and public health applications, this comprehensive exploration covers real-world uses and future possibilities of LLMs and generative AI in healthcare. With this book, you will: Understand the promise and challenges of LLMs in healthcare Learn the inner workings of LLMs and generative AI Explore automation of healthcare use cases for improved operations and patient care using LLMs Dive into patient experiences and clinical decision-making using generative AI Review future applications in pharmaceutical R&D, public health, and genomics Understand ethical considerations and responsible development of LLMs in healthcare "The authors illustrate generative's impact on drug development, presenting real-world examples of its ability to accelerate processes and improve outcomes across the pharmaceutical industry."--Harsh Pandey, VP, Data Analytics & Business Insights, Medidata-Dassault Kerrie Holley is a retired Google tech executive, IBM Fellow, and VP/CTO at Cisco. Holley's extensive experience includes serving as the first Technology Fellow at United Health Group (UHG), Optum, where he focused on advancing and applying AI, deep learning, and natural language processing in healthcare. Manish Mathur brings over two decades of expertise at the crossroads of healthcare and technology. A former executive at Google and Johnson & Johnson, he now serves as an independent consultant and advisor. He guides payers, providers, and life sciences companies in crafting cutting-edge healthcare solutions.

Data Analytics in Bioinformatics

Author : Rabinarayan Satpathy
Publisher : John Wiley & Sons
ISBN 13 : 111978560X
Total Pages : 433 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Data Analytics in Bioinformatics by : Rabinarayan Satpathy

Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Uncaring

Author : Robert Pearl
Publisher : PublicAffairs
ISBN 13 : 1541758250
Total Pages : 400 pages
Book Rating : 4.5/5 (417 download)

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Book Synopsis Uncaring by : Robert Pearl

Download or read book Uncaring written by Robert Pearl and published by PublicAffairs. This book was released on 2021-05-18 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doctors are taught how to cure people. But they don’t always know how to care for them. Hardly anyone is happy with American healthcare these days. Patients are getting sicker and going bankrupt from medical bills. Doctors are burning out and making dangerous mistakes. Both parties blame our nation’s outdated and dysfunctional healthcare system. But that’s only part of the problem. In this important and timely book, Dr. Robert Pearl shines a light on the unseen and often toxic culture of medicine. Today’s physicians have a surprising disdain for technology, an unhealthy obsession with status, and an increasingly complicated relationship with their patients. All of this can be traced back to their earliest experiences in medical school, where doctors inherit a set of norms, beliefs, and expectations that shape almost every decision they make, with profound consequences for the rest of us. Uncaring draws an original and revealing portrait of what it’s actually like to be a doctor. It illuminates the complex and intimidating world of medicine for readers, and in the end offers a clear plan to save American healthcare.

Artificial Intelligence

Author : Sandeep Reddy
Publisher : CRC Press
ISBN 13 : 1000216845
Total Pages : 353 pages
Book Rating : 4.0/5 (2 download)

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Book Synopsis Artificial Intelligence by : Sandeep Reddy

Download or read book Artificial Intelligence written by Sandeep Reddy and published by CRC Press. This book was released on 2020-12-02 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Explainable AI in Healthcare and Medicine

Author : Arash Shaban-Nejad
Publisher : Springer Nature
ISBN 13 : 3030533522
Total Pages : 344 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Explainable AI in Healthcare and Medicine by : Arash Shaban-Nejad

Download or read book Explainable AI in Healthcare and Medicine written by Arash Shaban-Nejad and published by Springer Nature. This book was released on 2020-11-02 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Featuring selected papers from the 2020 Health Intelligence Workshop, held as part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference, it offers an overview of the issues, challenges, and opportunities in the field, along with the latest research findings. Discussing a wide range of practical applications, it makes the emerging topics of digital health and explainable AI in health care and medicine accessible to a broad readership. The availability of explainable and interpretable models is a first step toward building a culture of transparency and accountability in health care. As such, this book provides information for scientists, researchers, students, industry professionals, public health agencies, and NGOs interested in the theory and practice of computational models of public and personalized health intelligence.