Explainable Ai In Healthcare

Explainable Ai In Healthcare Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Explainable Ai In Healthcare book. This book definitely worth reading, it is an incredibly well-written.

Explainable AI in Healthcare and Medicine

Arash Shaban-Nejad,Martin Michalowski,David L. Buckeridge
Explainable AI in Healthcare and Medicine Book PDF

Author : Arash Shaban-Nejad,Martin Michalowski,David L. Buckeridge
Publisher : Springer Nature
Page : 344 pages
File Size : 54,5 Mb
Release : 2020-11-02
Category : Technology & Engineering
ISBN : 9783030533526

Get Book

Explainable AI in Healthcare and Medicine by Arash Shaban-Nejad,Martin Michalowski,David L. Buckeridge Pdf

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.

Principles and Methods of Explainable Artificial Intelligence in Healthcare

Albuquerque, Victor Hugo C. de,Srinivasu, P. Naga,Bhoi, Akash Kumar,Briones, Alfonso Gonza?lez
Principles and Methods of Explainable Artificial Intelligence in Healthcare Book PDF

Author : Albuquerque, Victor Hugo C. de,Srinivasu, P. Naga,Bhoi, Akash Kumar,Briones, Alfonso Gonza?lez
Publisher : IGI Global
Page : 347 pages
File Size : 53,8 Mb
Release : 2022-05-20
Category : Computers
ISBN : 9781668437926

Get Book

Principles and Methods of Explainable Artificial Intelligence in Healthcare by Albuquerque, Victor Hugo C. de,Srinivasu, P. Naga,Bhoi, Akash Kumar,Briones, Alfonso Gonza?lez Pdf

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.

Explainable AI in Healthcare

Mehul S Raval,Mohendra Roy,Tolga Kaya,Rupal Kapdi
Explainable AI in Healthcare Book PDF

Author : Mehul S Raval,Mohendra Roy,Tolga Kaya,Rupal Kapdi
Publisher : CRC Press
Page : 346 pages
File Size : 51,5 Mb
Release : 2023-07-17
Category : Medical
ISBN : 9781000906400

Get Book

Explainable AI in Healthcare by Mehul S Raval,Mohendra Roy,Tolga Kaya,Rupal Kapdi Pdf

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

Embedded Systems and Artificial Intelligence

Vikrant Bhateja,Suresh Chandra Satapathy,Hassan Satori
Embedded Systems and Artificial Intelligence Book PDF

Author : Vikrant Bhateja,Suresh Chandra Satapathy,Hassan Satori
Publisher : Springer Nature
Page : 880 pages
File Size : 51,8 Mb
Release : 2020-04-07
Category : Technology & Engineering
ISBN : 9789811509476

Get Book

Embedded Systems and Artificial Intelligence by Vikrant Bhateja,Suresh Chandra Satapathy,Hassan Satori Pdf

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.

Handbook of Artificial Intelligence in Healthcare

Chee-Peng Lim,Yen-Wei Chen,Ashlesha Vaidya,Charu Mahorkar,Lakhmi C. Jain
Handbook of Artificial Intelligence in Healthcare Book PDF

Author : Chee-Peng Lim,Yen-Wei Chen,Ashlesha Vaidya,Charu Mahorkar,Lakhmi C. Jain
Publisher : Springer Nature
Page : 429 pages
File Size : 50,8 Mb
Release : 2021-11-26
Category : Technology & Engineering
ISBN : 9783030836207

Get Book

Handbook of Artificial Intelligence in Healthcare by Chee-Peng Lim,Yen-Wei Chen,Ashlesha Vaidya,Charu Mahorkar,Lakhmi C. Jain Pdf

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: Interpreting, Explaining and Visualizing Deep Learning

Wojciech Samek,Grégoire Montavon,Andrea Vedaldi,Lars Kai Hansen,Klaus-Robert Müller
Explainable AI Interpreting Explaining and Visualizing Deep Learning Book PDF

Author : Wojciech Samek,Grégoire Montavon,Andrea Vedaldi,Lars Kai Hansen,Klaus-Robert Müller
Publisher : Springer Nature
Page : 435 pages
File Size : 55,6 Mb
Release : 2019-09-10
Category : Computers
ISBN : 9783030289546

Get Book

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning by Wojciech Samek,Grégoire Montavon,Andrea Vedaldi,Lars Kai Hansen,Klaus-Robert Müller Pdf

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.

The AI Book

Ivana Bartoletti,Anne Leslie,Shân M. Millie
The AI Book Book PDF

Author : Ivana Bartoletti,Anne Leslie,Shân M. Millie
Publisher : John Wiley & Sons
Page : 782 pages
File Size : 41,7 Mb
Release : 2020-04-09
Category : Business & Economics
ISBN : 9781119551928

Get Book

The AI Book by Ivana Bartoletti,Anne Leslie,Shân M. Millie Pdf

Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important

Explainable AI in Health Informatics

Rajanikanth Aluvalu,Mayuri Mehta,Patrick Siarry
Explainable AI in Health Informatics Book PDF

Author : Rajanikanth Aluvalu,Mayuri Mehta,Patrick Siarry
Publisher : Springer
Page : 0 pages
File Size : 47,7 Mb
Release : 2024-08-19
Category : Computers
ISBN : 9819737044

Get Book

Explainable AI in Health Informatics by Rajanikanth Aluvalu,Mayuri Mehta,Patrick Siarry Pdf

This book provides a comprehensive review of the latest research in the area of explainable artificial intelligence (XAI) in health informatics. It focuses on how explainable AI models can work together with humans to assist them in decision-making, leading to improved diagnosis and prognosis in healthcare. This book includes a collection of techniques and systems of XAI in health informatics and gives a wider perspective about the impact created by them. The book covers the different aspects, such as robotics, informatics, drugs, patients, etc., related to XAI in healthcare. The book is suitable for both beginners and advanced AI practitioners, including students, academicians, researchers, and industry professionals. It serves as an excellent reference for undergraduate and graduate-level courses on AI for medicine/healthcare or XAI for medicine/healthcare. Medical institutions can also utilize this book as reference material and provide tutorials to medical professionals on how the XAI techniques can contribute to trustworthy diagnosis and prediction of the diseases.

Deep Learning Techniques for Biomedical and Health Informatics

Basant Agarwal,Valentina Emilia Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma
Deep Learning Techniques for Biomedical and Health Informatics Book PDF

Author : Basant Agarwal,Valentina Emilia Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma
Publisher : Academic Press
Page : 367 pages
File Size : 52,5 Mb
Release : 2020-01-14
Category : Science
ISBN : 9780128190623

Get Book

Deep Learning Techniques for Biomedical and Health Informatics by Basant Agarwal,Valentina Emilia Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma Pdf

Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis

Explainable AI with Python

Leonida Gianfagna,Antonio Di Cecco
Explainable AI with Python Book PDF

Author : Leonida Gianfagna,Antonio Di Cecco
Publisher : Springer Nature
Page : 202 pages
File Size : 53,9 Mb
Release : 2021-04-28
Category : Computers
ISBN : 9783030686406

Get Book

Explainable AI with Python by Leonida Gianfagna,Antonio Di Cecco Pdf

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.

Artificial Intelligence in Healthcare

Adam Bohr,Kaveh Memarzadeh
Artificial Intelligence in Healthcare Book PDF

Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Page : 385 pages
File Size : 47,5 Mb
Release : 2020-06-21
Category : Computers
ISBN : 9780128184394

Get Book

Artificial Intelligence in Healthcare by Adam Bohr,Kaveh Memarzadeh Pdf

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 Artificial Intelligence (XAI) in Healthcare

Utku Kose,Nilgun Sengoz,Xi Chen,Jose Antonio Marmolejo Saucedo
Explainable Artificial Intelligence XAI in Healthcare Book PDF

Author : Utku Kose,Nilgun Sengoz,Xi Chen,Jose Antonio Marmolejo Saucedo
Publisher : CRC Press
Page : 251 pages
File Size : 54,6 Mb
Release : 2024-04-23
Category : Medical
ISBN : 9781040020456

Get Book

Explainable Artificial Intelligence (XAI) in Healthcare by Utku Kose,Nilgun Sengoz,Xi Chen,Jose Antonio Marmolejo Saucedo Pdf

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.

Deep Learning in Gaming and Animations

Vikas Chaudhary,Moolchand Sharma,Prerna Sharma,Deevyankar Agarwal
Deep Learning in Gaming and Animations Book PDF

Author : Vikas Chaudhary,Moolchand Sharma,Prerna Sharma,Deevyankar Agarwal
Publisher : CRC Press
Page : 180 pages
File Size : 55,5 Mb
Release : 2021-12-07
Category : Computers
ISBN : 9781000504378

Get Book

Deep Learning in Gaming and Animations by Vikas Chaudhary,Moolchand Sharma,Prerna Sharma,Deevyankar Agarwal Pdf

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.

AI-First Healthcare

Kerrie L. Holley,Siupo Becker M.D.
AI First Healthcare Book PDF

Author : Kerrie L. Holley,Siupo Becker M.D.
Publisher : "O'Reilly Media, Inc."
Page : 222 pages
File Size : 43,7 Mb
Release : 2021-04-19
Category : Business & Economics
ISBN : 9781492063124

Get Book

AI-First Healthcare by Kerrie L. Holley,Siupo Becker M.D. Pdf

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

Intelligent Data Engineering and Automated Learning – IDEAL 2021

Hujun Yin,David Camacho,Peter Tino,Richard Allmendinger,Antonio J. Tallón-Ballesteros,Ke Tang,Sung-Bae Cho,Paulo Novais,Susana Nascimento
Intelligent Data Engineering and Automated Learning IDEAL 2021 Book PDF

Author : Hujun Yin,David Camacho,Peter Tino,Richard Allmendinger,Antonio J. Tallón-Ballesteros,Ke Tang,Sung-Bae Cho,Paulo Novais,Susana Nascimento
Publisher : Springer Nature
Page : 663 pages
File Size : 44,6 Mb
Release : 2021-11-23
Category : Computers
ISBN : 9783030916084

Get Book

Intelligent Data Engineering and Automated Learning – IDEAL 2021 by Hujun Yin,David Camacho,Peter Tino,Richard Allmendinger,Antonio J. Tallón-Ballesteros,Ke Tang,Sung-Bae Cho,Paulo Novais,Susana Nascimento Pdf

This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021, which took place during November 25-27, 2021. The conference was originally planned to take place in Manchester, UK, but was held virtually due to the COVID-19 pandemic. The 61 full papers included in this book were carefully reviewed and selected from 85 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing.