Explainable Artificial Intelligence Xai In Healthcare
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Principles And Methods Of Explainable Artificial Intelligence In Healthcare
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Author : Albuquerque, Victor Hugo C. de
language : en
Publisher: IGI Global
Release Date : 2022-05-20
Principles And Methods Of Explainable Artificial Intelligence In Healthcare written by Albuquerque, Victor Hugo C. de and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-20 with Computers categories.
Explainable artificial intelligence is proficient in operating and analyzing the unconstrainted environment in fields like robotic medicine, robotic treatment, and robotic surgery, which rely on computational vision for analyzing complex situations. Explainable artificial intelligence is a well-structured customizable technology that makes it possible to generate promising unbiased outcomes. The model’s adaptability facilitates the management of heterogeneous healthcare data and the visualization of biological structures through virtual reality. Explainable artificial intelligence has newfound applications in the healthcare industry, such as clinical trial matching, continuous healthcare monitoring, probabilistic evolutions, and evidence-based mechanisms. Principles and Methods of Explainable Artificial Intelligence in Healthcare discusses explainable artificial intelligence and its applications in healthcare, providing a broad overview of state-of-the-art approaches for accurate analysis and diagnosis. The book also encompasses computational vision processing techniques that handle complex data like physiological information, electronic healthcare records, and medical imaging data that assist in earlier prediction. Covering topics such as neural networks and disease detection, this reference work is ideal for industry professionals, practitioners, academicians, researchers, scholars, instructors, and students.
Deep Learning In Gaming And Animations
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Author : Vikas Chaudhary
language : en
Publisher: CRC Press
Release Date : 2021-12-07
Deep Learning In Gaming And Animations written by Vikas Chaudhary and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-07 with Computers categories.
Over the last decade, progress in deep learning has had a profound and transformational effect on many complex problems, including speech recognition, machine translation, natural language understanding, and computer vision. As a result, computers can now achieve human-competitive performance in a wide range of perception and recognition tasks. Many of these systems are now available to the programmer via a range of so-called cognitive services. More recently, deep reinforcement learning has achieved ground-breaking success in several complex challenges. This book makes an enormous contribution to this beautiful, vibrant area of study: an area that is developing rapidly both in breadth and depth. Deep learning can cope with a broader range of tasks (and perform those tasks to increasing levels of excellence). This book lays a good foundation for the core concepts and principles of deep learning in gaming and animation, walking you through the fundamental ideas with expert ease. This book progresses in a step-by-step manner. It reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into its applications. Also, some chapters introduce and cover novel ideas about how artificial intelligence (AI), deep learning, and machine learning have changed the world in gaming and animation. It gives us the idea that AI can also be applied in gaming, and there are limited textbooks in this area. This book comprehensively addresses all the aspects of AI and deep learning in gaming. Also, each chapter follows a similar structure so that students, teachers, and industry experts can orientate themselves within the text. There are few books in the field of gaming using AI. Deep Learning in Gaming and Animations teaches you how to apply the power of deep learning to build complex reasoning tasks. After being exposed to the foundations of machine and deep learning, you will use Python to build a bot and then teach it the game's rules. This book also focuses on how different technologies have revolutionized gaming and animation with various illustrations.
Explainable Artificial Intelligence Xai In Healthcare
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Author : Utku Kose
language : en
Publisher: CRC Press
Release Date : 2024-04-23
Explainable Artificial Intelligence Xai In Healthcare written by Utku Kose and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-23 with Medical categories.
This book highlights the use of explainable artificial intelligence (XAI) for healthcare problems, in order to improve trustworthiness, performance and sustainability levels in the context of applications. Explainable Artificial Intelligence (XAI) in Healthcare adopts the understanding that AI solutions should not only have high accuracy performance, but also be transparent, understandable and reliable from the end user's perspective. The book discusses the techniques, frameworks, and tools to effectively implement XAI methodologies in critical problems of healthcare field. The authors offer different types of solutions, evaluation methods and metrics for XAI and reveal how the concept of explainability finds a response in target problem coverage. The authors examine the use of XAI in disease diagnosis, medical imaging, health tourism, precision medicine and even drug discovery. They also point out the importance of user perspectives and value of the data used in target problems. Finally, the authors also ensure a well-defined future perspective for advancing XAI in terms of healthcare. This book will offer great benefits to students at the undergraduate and graduate levels and researchers. The book will also be useful for industry professionals and clinicians who perform critical decision-making tasks.
Handbook Of Artificial Intelligence In Healthcare
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Author : Chee-Peng Lim
language : en
Publisher: Springer Nature
Release Date : 2021-11-26
Handbook Of Artificial Intelligence In Healthcare written by Chee-Peng Lim and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-26 with Technology & Engineering categories.
Artificial Intelligence (AI) has transformed many aspects of our daily activities. Health and well-being of humans stand as one of the key domains where AI has achieved significant progresses, saving time, costs, and potentially lives, as well as fostering economic resilience, particularly under the COVID-19 pandemic environments. This book is a sequel of the Handbook of Artificial Intelligence in Healthcare. The first volume of the Handbook is dedicated to present advances and applications of AI methodologies in several specific areas, i.e., signal, image, and video processing as well as information and data analytics. In this second volume of the Handbook, general practicality challenges and future prospects of AI methodologies pertaining to healthcare and related domains are presented in Part 1 and Part 2, respectively. It is envisaged that the selected studies will provide readers a general perspective on the issues, challenges, and opportunities in designing, developing, and implementing AI-based tools and solutions in the healthcare sector, bringing benefits to transform and advance health and well-being development of humans..
Explainable Ai Within The Digital Transformation And Cyber Physical Systems
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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer Nature
Release Date : 2021-10-30
Explainable Ai Within The Digital Transformation And Cyber Physical Systems written by Moamar Sayed-Mouchaweh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-30 with Technology & Engineering categories.
This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.
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
Explainable Ai With Python
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Author : Leonida Gianfagna
language : en
Publisher: Springer Nature
Release Date : 2021-04-28
Explainable Ai With Python written by Leonida Gianfagna and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Computers categories.
This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linear and logistic regression, deep learning neural networks, natural language processing and image recognition, among the others. Progress in Machine Learning is increasing the use of artificial agents to perform critical tasks previously handled by humans (healthcare, legal and finance, among others). While the principles that guide the design of these agents are understood, most of the current deep-learning models are "opaque" to human understanding. Explainable AI with Python fills the current gap in literature on this emerging topic by taking both a theoretical and a practical perspective, making the reader quickly capable of working with tools and code for Explainable AI. Beginning with examples of what Explainable AI (XAI) is and why it is needed in the field, the book details different approaches to XAI depending on specific context and need. Hands-on work on interpretable models with specific examples leveraging Python are then presented, showing how intrinsic interpretable models can be interpreted and how to produce “human understandable” explanations. Model-agnostic methods for XAI are shown to produce explanations without relying on ML models internals that are “opaque.” Using examples from Computer Vision, the authors then look at explainable models for Deep Learning and prospective methods for the future. Taking a practical perspective, the authors demonstrate how to effectively use ML and XAI in science. The final chapter explains Adversarial Machine Learning and how to do XAI with adversarial examples.
Explainable Ai In Healthcare
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Author : Mehul S Raval
language : en
Publisher: CRC Press
Release Date : 2023-07-17
Explainable Ai In Healthcare written by Mehul S Raval and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-17 with Medical categories.
This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering. This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care
Interpretable Machine Learning
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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020
Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.
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.
Explainable Artificial Intelligence In The Healthcare Industry
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Author : Abhishek Kumar
language : en
Publisher: John Wiley & Sons
Release Date : 2025-04-08
Explainable Artificial Intelligence In The Healthcare Industry written by Abhishek Kumar and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-08 with Computers categories.
Discover the essential insights and practical applications of explainable AI in healthcare that will empower professionals and enhance patient trust with Explainable AI in the Healthcare Industry, a must-have resource. Explainable AI (XAI) has significant implications for the healthcare industry, where trust, accountability, and interpretability are crucial factors for the adoption of artificial intelligence. XAI techniques in healthcare aim to provide clear and understandable explanations for AI-driven decisions, helping healthcare professionals, patients, and regulatory bodies to better comprehend and trust the AI models’ outputs. Explainable AI in the Healthcare Industry presents a comprehensive exploration of the critical role of explainable AI in revolutionizing the healthcare industry. With the rapid integration of AI-driven solutions in medical practice, understanding how these models arrive at their decisions is of paramount importance. The book delves into the principles, methodologies, and practical applications of XAI techniques specifically tailored for healthcare settings.