Download or read book Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry written by Grover, Veena and published by IGI Global. This book was released on 2024-06-05 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications, and regulatory compliance. As stakeholders in these critical sectors seek clarity and understanding, Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry provides a reliable resource to discover new solutions. This book serves as a comprehensive guide, unraveling the complexities of explainable artificial intelligence (XAI) and its pivotal role in transforming healthcare and pharmaceutical practices. Demystifying AI algorithms and revealing their decision-making mechanisms equips readers with the foundational knowledge needed to confidently navigate AI integration in these domains. From healthcare professionals to policymakers, its insights cater to a diverse audience, fostering cross-disciplinary collaboration and facilitating informed decision-making.
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
Download or read book Artificial Intelligence in Drug Discovery written by Nathan Brown and published by Royal Society of Chemistry. This book was released on 2020-11-04 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.
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.
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
Download or read book Cybersecurity and Data Management Innovations for Revolutionizing Healthcare written by Murugan, Thangavel and published by IGI Global. This book was released on 2024-07-23 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: In todays digital age, the healthcare industry is undergoing a paradigm shift towards embracing innovative technologies to enhance patient care, improve efficiency, and ensure data security. With the increasing adoption of electronic health records, telemedicine, and AI-driven diagnostics, robust cybersecurity measures and advanced data management strategies have become paramount. Protecting sensitive patient information from cyber threats is critical and maintaining effective data management practices is essential for ensuring the integrity, accuracy, and availability of vast amounts of healthcare data. Cybersecurity and Data Management Innovations for Revolutionizing Healthcare delves into the intersection of healthcare, data management, cybersecurity, and emerging technologies. It brings together a collection of insightful chapters that explore the transformative potential of these innovations in revolutionizing healthcare practices around the globe. Covering topics such as advanced analytics, data breach detection, and privacy preservation, this book is an essential resource for healthcare professionals, researchers, academicians, healthcare professionals, data scientists, cybersecurity experts, and more.
Download or read book Embedded Systems and Artificial Intelligence written by Vikrant Bhateja and published by Springer Nature. This book was released on 2020-04-07 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected research papers presented at the First International Conference on Embedded Systems and Artificial Intelligence (ESAI 2019), held at Sidi Mohamed Ben Abdellah University, Fez, Morocco, on 2–3 May 2019. Highlighting the latest innovations in Computer Science, Artificial Intelligence, Information Technologies, and Embedded Systems, the respective papers will encourage and inspire researchers, industry professionals, and policymakers to put these methods into practice.
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
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.
Download or read book Artificial Intelligence in Healthcare written by Lalit Garg and published by Springer Nature. This book was released on 2021-10-29 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the analytics and optimization issues in healthcare systems, proposes new approaches, and presents applications of innovative approaches in real facilities. In the past few decades, there has been an exponential rise in the application of swarm intelligence techniques for solving complex and intricate problems arising in healthcare. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas. The primary objective of this book is to bring forward thorough, in-depth, and well-focused developments of hybrid variants of swarm intelligence algorithms and their applications in healthcare systems.
Download or read book Artificial Intelligence in Medicine written by Niklas Lidströmer and published by Springer. This book was released on 2022-03-17 with total page 1816 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a structured and analytical guide to the use of artificial intelligence in medicine. Covering all areas within medicine, the chapters give a systemic review of the history, scientific foundations, present advances, potential trends, and future challenges of artificial intelligence within a healthcare setting. Artificial Intelligence in Medicine aims to give readers the required knowledge to apply artificial intelligence to clinical practice. The book is relevant to medical students, specialist doctors, and researchers whose work will be affected by artificial intelligence.
Download or read book Medical Imaging Informatics written by Alex A.T. Bui and published by Springer Science & Business Media. This book was released on 2009-12-01 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Imaging Informatics provides an overview of this growing discipline, which stems from an intersection of biomedical informatics, medical imaging, computer science and medicine. Supporting two complementary views, this volume explores the fundamental technologies and algorithms that comprise this field, as well as the application of medical imaging informatics to subsequently improve healthcare research. Clearly written in a four part structure, this introduction follows natural healthcare processes, illustrating the roles of data collection and standardization, context extraction and modeling, and medical decision making tools and applications. Medical Imaging Informatics identifies core concepts within the field, explores research challenges that drive development, and includes current state-of-the-art methods and strategies.
Download or read book Explainable AI Interpreting Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Download or read book AI Healthcare Applications and Security Ethical and Legal Considerations written by Singla, Babita and published by IGI Global. This book was released on 2024-08-05 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) technology has led to the creation of many opportunities in the field of healthcare. Like other industries, stakeholders in the healthcare sector stand to benefit tremendously from its adoption. The multifaceted benefits associated with AI are something that makes the adoption of technology constructive for the sector. That said, it is equally important to take care of the ethical, security, and safety challenges related to AI applications. AI Healthcare Applications and Security, Ethical, and Legal Considerations discusses in detail the various facets of AI integration in the healthcare sector. This book offers comprehensive information on how to integrate AI into the healthcare sector safely and ethically. Covering topics such as cybersecurity, machine learning models, and public policy, this book is an excellent resource for healthcare professionals and administrators, researchers, ethicists, legal scholars, healthcare policy makers and regulators, medical informatics and IT professionals, educators, bioethics professionals, academicians, and more.
Download or read book Advances in Computational Intelligence for the Healthcare Industry 4 0 written by Shah, Imdad Ali and published by IGI Global. This book was released on 2024-04-26 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the dynamic environment of healthcare, the fusion of Computational Intelligence and Healthcare Industry 4.0 has enabled remarkable advancements in disease detection and analysis. However, a critical challenge persists – the limitations of current computational intelligence approaches in dealing with small sample sizes. This setback hampers the performance of these innovative models, hindering their potential impact on medical applications. As we stand at the crossroads of technological innovation and healthcare evolution, the need for a solution becomes paramount. Advances in Computational Intelligence for the Healthcare Industry 4.0 is a comprehensive guide addressing the very heart of this challenge. Designed for academics, researchers, healthcare professionals, and stakeholders in Healthcare Industry 4.0, this book serves as a source of innovation. It not only illuminates the complexities of computational intelligence in healthcare but also provides a roadmap for overcoming the limitations posed by small sample sizes. From fundamental principles to innovative concepts, this book offers a holistic perspective, shaping the future of healthcare through the lens of computational intelligence and Healthcare Industry 4.0.
Download or read book Encyclopedia of Data Science and Machine Learning written by Wang, John and published by IGI Global. This book was released on 2023-01-20 with total page 3296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Download or read book Machine Learning for Health Informatics written by Andreas Holzinger and published by Springer. This book was released on 2016-12-09 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.
