Explainable Artificial Intelligence A Practical Guide
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Explainable Artificial Intelligence A Practical Guide
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Author : Parikshit Narendra Mahalle
language : en
Publisher: CRC Press
Release Date : 2024-12-02
Explainable Artificial Intelligence A Practical Guide written by Parikshit Narendra Mahalle and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-02 with Computers categories.
This book explores the growing focus on artificial intelligence (AI) systems in both industry and academia. It evaluates and justifies AI applications while enhancing trust in AI outcomes and aiding comprehension of AI feature development. Key topics include an overview of explainable AI, black box model understanding, interpretability techniques, practical XAI applications, and future trends and challenges in XAI. Technical topics discussed in the book include: Explainable AI overview Understanding black box models Techniques for model interpretability Practical applications of XAI Future trends and challenges in XAI
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 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 Artificial Intelligence
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Author : Luca Longo
language : en
Publisher: Springer Nature
Release Date : 2023-10-20
Explainable Artificial Intelligence written by Luca Longo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-20 with Computers categories.
Chapters “Finding Spurious Correlations with Function-Semantic Contrast Analysis” and “Explaining Socio-Demographic and Behavioral Patterns of Vaccination Against the Swine Flu (H1N1) Pandemic” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Explainable Artificial Intelligence For Biomedical And Healthcare Applications
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Author : Aditya Khamparia
language : en
Publisher: CRC Press
Release Date : 2024-10-09
Explainable Artificial Intelligence For Biomedical And Healthcare Applications written by Aditya Khamparia and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-09 with Technology & Engineering categories.
This reference text helps us understand how the concepts of explainable artificial intelligence (XAI) are used in the medical and healthcare sectors. The text discusses medical robotic systems using XAI and physical devices having autonomous behaviors for medical operations. It explores the usage of XAI for analyzing different types of unique data sets for medical image analysis, medical image registration, medical data synthesis, and information discovery. It covers important topics including XAI for biometric security, genomics, and medical disease diagnosis. This book: • Provides an excellent foundation for the core concepts and principles of explainable AI in biomedical and healthcare applications. • Covers explainable AI for robotics and autonomous systems. • Discusses usage of explainable AI in medical image analysis, medical image registration, and medical data synthesis. • Examines biometrics security-assisted applications and their integration using explainable AI. The text will be useful for graduate students, professionals, and academic researchers in diverse areas such as electrical engineering, electronics and communication engineering, biomedical engineering, and computer science.
Artificial Intelligence In Medicine A Practical Guide For Clinicians
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Author : Campion Quinn
language : en
Publisher: World Scientific
Release Date : 2024-02-06
Artificial Intelligence In Medicine A Practical Guide For Clinicians written by Campion Quinn and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-06 with Medical categories.
'Artificial Intelligence in Medicine' is a comprehensive guide exploring the transformative impact of artificial intelligence (AI) in healthcare. The book delves into the foundational concepts and historical development of AI in medicine, highlighting data collection, preprocessing, and feature extraction crucial for medical applications. It showcases the benefits of AI, such as accurate diagnoses and personalized treatments, while addressing ethical and regulatory considerations.The book examines the practical aspects of AI implementation in clinical practice and emphasizes the human aspect of AI in healthcare and patient engagement. Readers can gain insights into the role of AI in clinical decision support, collaborative learning, and knowledge sharing. It concludes with a glimpse into the future of AI-driven healthcare, exploring the emerging technologies and trends in the rapidly evolving field of AI in medicine.
Explainable And Responsible Artificial Intelligence In Healthcare
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Author : Rishabha Malviya
language : en
Publisher: John Wiley & Sons
Release Date : 2025-04-01
Explainable And Responsible Artificial Intelligence In Healthcare written by Rishabha Malviya 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 2025-04-01 with Computers categories.
This book presents the fundamentals of explainable artificial intelligence (XAI) and responsible artificial intelligence (RAI), discussing their potential to enhance diagnosis, treatment, and patient outcomes. This book explores the transformative potential of explainable artificial intelligence (XAI) and responsible AI (RAI) in healthcare. It provides a roadmap for navigating the complexities of healthcare-based AI while prioritizing patient safety and well-being. The content is structured to highlight topics on smart health systems, neuroscience, diagnostic imaging, and telehealth. The book emphasizes personalized treatment and improved patient outcomes in various medical fields. In addition, this book discusses osteoporosis risk, neurological treatment, and bone metastases. Each chapter provides a distinct viewpoint on how XAI and RAI approaches can help healthcare practitioners increase diagnosis accuracy, optimize treatment plans, and improve patient outcomes. Readers will find the book: explains recent XAI and RAI breakthroughs in the healthcare system; discusses essential architecture with computational advances ranging from medical imaging to disease diagnosis; covers the latest developments and applications of XAI and RAI-based disease management applications; demonstrates how XAI and RAI can be utilized in healthcare and what problems the technology faces in the future. Audience The main audience for this book is targeted to scientists, healthcare professionals, biomedical industries, hospital management, engineers, and IT professionals interested in using AI to improve human health.
Artificial Intelligence Xxxix
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Author : Max Bramer
language : en
Publisher: Springer Nature
Release Date : 2022-12-05
Artificial Intelligence Xxxix written by Max Bramer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-05 with Computers categories.
This book constitutes the proceedings of the 42nd SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2022, which was held in Cambridge, UK, in December 2022. The 20 full papers and 11 short papers presented in this volume were carefully reviewed and selected from 40 submissions. The volume includes technical papers presenting new and innovative developments in the field as well as application papers presenting innovative applications of AI techniques in a number of subject domains. The papers are organized in the following topical sections: best technical paper; best application paper; AI for health and medicine; AI for scientific discovery and decision making; AI for industrial applications; feasibility studies of applied AI; and short papers.
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.
Explainable Artificial Intelligence For Cyber Security
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Author : Mohiuddin Ahmed
language : en
Publisher: Springer Nature
Release Date : 2022-04-18
Explainable Artificial Intelligence For Cyber Security written by Mohiuddin Ahmed and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-18 with Computers categories.
This book presents that explainable artificial intelligence (XAI) is going to replace the traditional artificial, machine learning, deep learning algorithms which work as a black box as of today. To understand the algorithms better and interpret the complex networks of these algorithms, XAI plays a vital role. In last few decades, we have embraced AI in our daily life to solve a plethora of problems, one of the notable problems is cyber security. In coming years, the traditional AI algorithms are not able to address the zero-day cyber attacks, and hence, to capitalize on the AI algorithms, it is absolutely important to focus more on XAI. Hence, this book serves as an excellent reference for those who are working in cyber security and artificial intelligence.