Generative Ai For Healthcare
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Ai First Healthcare
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Author : Kerrie L. Holley
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-04-19
Ai First Healthcare written by Kerrie L. Holley and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-19 with Business & Economics categories.
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
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
Smart Healthcare Systems
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Author : Adwitiya Sinha
language : en
Publisher: CRC Press
Release Date : 2019-07-24
Smart Healthcare Systems written by Adwitiya Sinha and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-24 with Computers categories.
About the Book The book provides details of applying intelligent mining techniques for extracting and pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis and Treatment options Applications of Big Data and Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare and analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.
Digital Health Ai And Generative Ai In Healthcare
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Author : Terry Adirim
language : en
Publisher: Springer Nature
Release Date : 2025-04-25
Digital Health Ai And Generative Ai In Healthcare written by Terry Adirim and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-25 with Technology & Engineering categories.
The purpose of this title is to provide a comprehensive foundation for all medical professionals and healthcare-professions students in understanding Artificial Intelligence (AI). With the advent of generative AI, including the release of Open AI’s ChatGPT in 2022, the world entered a new age of rapid advancements in technology that will significantly change the way clinicians practice medicine, operate healthcare institutions, and conduct research. At the heart of this penetrating book is the idea that medical schools, medical training programs and other health education institutions must undertake a key role in developing AI literacy for clinicians across the spectrum of medical education that includes all health professions. Moreover, assert the authors, AI literacy should be incorporated within medical school curriculums as a core competency, as well as into graduate medical education training programs and continuing medical education courses. This timely and easy-to-read guide offers a wide range of chapters that discuss the core concepts and issues relating to AI in medicine, including a basic understanding of algorithms, machine learning, large language models and natural language processing, the limits and pitfalls of AI, ethical and legal issues, the evolving regulatory landscape around AI, as well as how AI is currently being used in healthcare, to name just several compelling topics. Additionally, AI technologies will change how medical school curriculums are delivered and how student competencies are assessed, maintain the authors. Therefore, medical educators will not only need to rethink how and what medical information is conveyed to students during formal instruction, but also must be prepared for AI-powered programs being used to assess students and trainees for the purpose of licensure and board certification. A timely and soon-to-be gold standard resource in the field, Digital Health, AI, and Generative AI: A Concise, Practical Guide for Clinicians will be of great interest to medical professionals, trainees, administrators, policymakers, and anyone interested in the fast-evolving intersection of digital technologies and healthcare.
Llms And Generative Ai For Healthcare
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Author : Kerrie Holley
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-08-20
Llms And Generative Ai For Healthcare written by Kerrie Holley and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-20 with Business & Economics categories.
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.
A Comprehensive Guide To Gen Ai In Healthcare Transformation 2025
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Author : Lakshman Kumar Jamili, Dr. Rahul Kumar
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
A Comprehensive Guide To Gen Ai In Healthcare Transformation 2025 written by Lakshman Kumar Jamili, Dr. Rahul Kumar 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.
brink of a technological revolution, driven by the rapid advancements in artificial intelligence. Among the most groundbreaking innovations is Generative AI (Gen AI), a powerful subset of AI that is transforming diagnostics, personalized medicine, clinical workflows, and patient engagement. By leveraging deep learning models, Gen AI is not only enhancing decision-making for healthcare professionals but also improving outcomes, reducing costs, and optimizing operational efficiency. This book, A Comprehensive Guide to Gen AI in Healthcare Transformation, explores how generative AI is reshaping every facet of healthcare. From AI-assisted drug discovery and predictive analytics to automated documentation and virtual health assistants, we delve into the practical applications, benefits, and challenges of this emerging technology. Beyond its technical capabilities, Gen AI also raises critical ethical, regulatory, and privacy concerns. As healthcare institutions adopt AI-driven solutions, questions about data security, bias mitigation, and regulatory compliance become more pressing. This book provides a balanced perspective, addressing both the immense potential and the responsibilities that come with integrating AI into healthcare systems. Our goal is to equip healthcare professionals, researchers, policymakers, and technology leaders with the knowledge and insights needed to harness Gen AI effectively. Whether you are exploring AI’s role in medical research or seeking ways to implement AI-driven solutions in clinical practice, this book serves as a comprehensive guide to navigating the future of healthcare innovation. The transformation is already underway. The question is no longer if AI will redefine healthcare but howwe can maximize its impact responsibly and effectively. Authors
Introduction To Deep Learning For Healthcare
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Author : Cao Xiao
language : en
Publisher: Springer Nature
Release Date : 2021-11-11
Introduction To Deep Learning For Healthcare written by Cao Xiao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-11 with Medical categories.
This textbook presents deep learning models and their healthcare applications. It focuses on rich health data and deep learning models that can effectively model health data. Healthcare data: Among all healthcare technologies, electronic health records (EHRs) had vast adoption and a significant impact on healthcare delivery in recent years. One crucial benefit of EHRs is to capture all the patient encounters with rich multi-modality data. Healthcare data include both structured and unstructured information. Structured data include various medical codes for diagnoses and procedures, lab results, and medication information. Unstructured data contain 1) clinical notes as text, 2) medical imaging data such as X-rays, echocardiogram, and magnetic resonance imaging (MRI), and 3) time-series data such as the electrocardiogram (ECG) and electroencephalogram (EEG). Beyond the data collected during clinical visits, patient self-generated/reported data start to grow thanks to wearable sensors’ increasing use. The authors present deep learning case studies on all data described. Deep learning models: Neural network models are a class of machine learning methods with a long history. Deep learning models are neural networks of many layers, which can extract multiple levels of features from raw data. Deep learning applied to healthcare is a natural and promising direction with many initial successes. The authors cover deep neural networks, convolutional neural networks, recurrent neural networks, embedding methods, autoencoders, attention models, graph neural networks, memory networks, and generative models. It’s presented with concrete healthcare case studies such as clinical predictive modeling, readmission prediction, phenotyping, x-ray classification, ECG diagnosis, sleep monitoring, automatic diagnosis coding from clinical notes, automatic deidentification, medication recommendation, drug discovery (drug property prediction and molecule generation), and clinical trial matching. This textbook targets graduate-level students focused on deep learning methods and their healthcare applications. It can be used for the concepts of deep learning and its applications as well. Researchers working in this field will also find this book to be extremely useful and valuable for their research.
Revolutionizing Healthcare 5 0 The Power Of Generative Ai
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Author : Pronaya Bhattacharya
language : en
Publisher: Springer Nature
Release Date : 2025-02-18
Revolutionizing Healthcare 5 0 The Power Of Generative Ai written by Pronaya Bhattacharya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-18 with Technology & Engineering categories.
This book serves as a critical resource that bridges the gap between burgeoning technology and its practical implementation. The book starts with an in-depth exploration of healthcare 5.0 principles, laying the foundation for the reader to understand the current shifts in healthcare paradigms. Then, it dives into the intricacies of generative models in healthcare, detailing how these algorithms work and the applications they serve. The book further delves into the subsets of generative machine learning and deep learning techniques in healthcare. As we move towards more complex applications, the book takes a turn to address the critical subject of interpretability and explainability in generative models, a topic that resonates profoundly given the life-critical nature of medical decisions. Finally, the book concludes with a robust discussion on the security and privacy concerns that accompany the deployment of GAI in real healthcare settings. By offering a multidimensional viewpoint—coupled with case studies, statistical analyses, and expert insights—the book ensures that the reader is left with a nuanced understanding of how GAI can be both a boon and a challenge in healthcare. As such, the proposed book serves as an indispensable resource for healthcare professionals, data scientists, researchers, and anyone invested in the future of healthcare and AI.
Artificial Intelligence And Machine Learning In Healthcare
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Author : Ankur Saxena
language : en
Publisher: Springer Nature
Release Date : 2021-05-06
Artificial Intelligence And Machine Learning In Healthcare written by Ankur Saxena and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-06 with Science categories.
This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.
Application Of Generative Ai In Healthcare Systems
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Author : Azadeh Zamanifar
language : en
Publisher: Springer Nature
Release Date : 2025-02-25
Application Of Generative Ai In Healthcare Systems written by Azadeh Zamanifar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-25 with Medical categories.
Generative AI has immensely influenced various fields, such as education, marketing, art and music, and especially healthcare. Generative AI can benefit the patient through various approaches. For instance, it can enhance the image qualities negatively affected by radiation reduction, preventing patients from needing to repeat the image-taking process. Also, the generation of one type of image from another more expensive one can help patients save funds. Generative AI facilitates the administrative process, letting the doctor focus more on the treatment process. It even goes further by helping medical professionals with diagnosis and decision- making, suggesting possible treatment plans according to the patient symptoms. This book introduces several practical GenAI healthcare applications, especially in medical imaging, pandemic prediction, synthetic data generation, clinical administration support, professional education, patient engagement, and clinical decision support, providing a review of efficient GenAI tools and frameworks in this area. GenAI empowers the treatment process through several methods; however, some ethical, privacy, and security challenges require attention. Despite the challenges presented, GenAI technological and inherited characteristics smooth the path of improvement for it in the future.