Biomedical Data Analysis And Processing Using Explainable Xai And Responsive Artificial Intelligence Rai

Biomedical Data Analysis And Processing Using Explainable Xai And Responsive Artificial Intelligence Rai 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 Biomedical Data Analysis And Processing Using Explainable Xai And Responsive Artificial Intelligence Rai book. This book definitely worth reading, it is an incredibly well-written.

Biomedical Data Analysis and Processing Using Explainable (XAI) and Responsive Artificial Intelligence (RAI)

Author : Aditya Khamparia,Deepak Gupta,Ashish Khanna,Valentina E. Balas
Publisher : Springer Nature
Page : 148 pages
File Size : 48,8 Mb
Release : 2022-04-09
Category : Technology & Engineering
ISBN : 9789811914768

Get Book

Biomedical Data Analysis and Processing Using Explainable (XAI) and Responsive Artificial Intelligence (RAI) by Aditya Khamparia,Deepak Gupta,Ashish Khanna,Valentina E. Balas Pdf

The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. It will discuss the advantages in dealing with big and complex data by using explainable AI concepts in the field of biomedical sciences. The book explains both positive as well as negative findings obtained by explainable AI techniques. It features real time experiences by physicians and medical staff for applied deep learning based solutions. The book will be extremely useful for researchers and practitioners in advancing their studies.

Medical Data Analysis and Processing using Explainable Artificial Intelligence

Author : Om Prakash Jena,Mrutyunjaya Panda,Utku Kose
Publisher : CRC Press
Page : 287 pages
File Size : 47,9 Mb
Release : 2023-11-02
Category : Technology & Engineering
ISBN : 9781000983654

Get Book

Medical Data Analysis and Processing using Explainable Artificial Intelligence by Om Prakash Jena,Mrutyunjaya Panda,Utku Kose Pdf

The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems. It will serve as an ideal reference text for graduate students and academic researchers in diverse fields of engineering including electrical, electronics and communication, computer, and biomedical. Presents explainable artificial intelligence (XAI) based machine analytics and deep learning in medical science. Discusses explainable artificial intelligence (XA)I with the Internet of Medical Things (IoMT) for healthcare applications. Covers algorithms, tools, and frameworks for explainable artificial intelligence on medical data. Explores the concepts of natural language processing and explainable artificial intelligence (XAI) on medical data processing. Discusses machine learning and deep learning scalability models in healthcare systems. This text focuses on data driven analysis and processing of advanced methods and techniques with the help of explainable artificial intelligence (XAI) algorithms. It covers machine learning, Internet of Things (IoT), and deep learning algorithms based on XAI techniques for medical data analysis and processing. The text will present different dimensions of XAI based computational intelligence applications. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.

Explainable Artificial Intelligence for Biomedical Applications

Author : Utku Kose,Deepak Gupta,Xi Chen
Publisher : CRC Press
Page : 421 pages
File Size : 46,6 Mb
Release : 2023-12-14
Category : Technology & Engineering
ISBN : 9781003810582

Get Book

Explainable Artificial Intelligence for Biomedical Applications by Utku Kose,Deepak Gupta,Xi Chen Pdf

Since its first appearance, artificial intelligence has been ensuring revolutionary outcomes in the context of real-world problems. At this point, it has strong relations with biomedical and today’s intelligent systems compete with human capabilities in medical tasks. However, advanced use of artificial intelligence causes intelligent systems to be black-box. That situation is not good for building trustworthy intelligent systems in medical applications. For a remarkable amount of time, researchers have tried to solve the black-box issue by using modular additions, which have led to the rise of the term: interpretable artificial intelligence. As the literature matured (as a result of, in particular, deep learning), that term transformed into explainable artificial intelligence (XAI). This book provides an essential edited work regarding the latest advancements in explainable artificial intelligence (XAI) for biomedical applications. It includes not only introductive perspectives but also applied touches and discussions regarding critical problems as well as future insights. Topics discussed in the book include: XAI for the applications with medical images XAI use cases for alternative medical data/task Different XAI methods for biomedical applications Reviews for the XAI research for critical biomedical problems. Explainable Artificial Intelligence for Biomedical Applications is ideal for academicians, researchers, students, engineers, and experts from the fields of computer science, biomedical, medical, and health sciences. It also welcomes all readers of different fields to be informed about use cases of XAI in black-box artificial intelligence. In this sense, the book can be used for both teaching and reference source purposes.

Explainable Artificial Intelligence

Author : Luca Longo
Publisher : Springer Nature
Page : 711 pages
File Size : 44,6 Mb
Release : 2023-12-05
Category : Computers
ISBN : 9783031440649

Get Book

Explainable Artificial Intelligence by Luca Longo Pdf

This three-volume set constitutes the refereed proceedings of the First World Conference on Explainable Artificial Intelligence, xAI 2023, held in Lisbon, Portugal, in July 2023. The 94 papers presented were thoroughly reviewed and selected from the 220 qualified submissions. They are organized in the following topical sections: ​ Part I: Interdisciplinary perspectives, approaches and strategies for xAI; Model-agnostic explanations, methods and techniques for xAI, Causality and Explainable AI; Explainable AI in Finance, cybersecurity, health-care and biomedicine. Part II: Surveys, benchmarks, visual representations and applications for xAI; xAI for decision-making and human-AI collaboration, for Machine Learning on Graphs with Ontologies and Graph Neural Networks; Actionable eXplainable AI, Semantics and explainability, and Explanations for Advice-Giving Systems. Part III: xAI for time series and Natural Language Processing; Human-centered explanations and xAI for Trustworthy and Responsible AI; Explainable and Interpretable AI with Argumentation, Representational Learning and concept extraction for xAI.

Medical Data Analysis and Processing Using Explainable Artificial Intelligence

Author : Anonim
Publisher : Unknown
Page : 0 pages
File Size : 40,5 Mb
Release : 2023
Category : Artificial intelligence
ISBN : 1003257720

Get Book

Medical Data Analysis and Processing Using Explainable Artificial Intelligence by Anonim Pdf

The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems. It will serve as an ideal reference text for graduate students and academic researchers in diverse fields of engineering including electrical, electronics and communication, computer, and biomedical Presents explainable artificial intelligence (XAI) based machine analytics and deep learning in medical science Discusses explainable artificial intelligence (XA)I with the Internet of Medical Things (IoMT) for healthcare applications Covers algorithms, tools, and frameworks for explainable artificial intelligence on medical data Explores the concepts of natural language processing and explainable artificial intelligence (XAI) on medical data processing Discusses machine learning and deep learning scalability models in healthcare systems This text focuses on data driven analysis and processing of advanced methods and techniques with the help of explainable artificial intelligence (XAI) algorithms. It covers machine learning, Internet of Things (IoT), and deep learning algorithms based on XAI techniques for medical data analysis and processing. The text will present different dimensions of XAI based computational intelligence applications. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.

Artificial intelligence in Pharmaceutical Sciences

Author : Mullaicharam Bhupathyraaj,K. Reeta Vijaya Rani,Musthafa Mohamed Essa
Publisher : CRC Press
Page : 181 pages
File Size : 50,8 Mb
Release : 2023-11-23
Category : Medical
ISBN : 9781000994551

Get Book

Artificial intelligence in Pharmaceutical Sciences by Mullaicharam Bhupathyraaj,K. Reeta Vijaya Rani,Musthafa Mohamed Essa Pdf

This cutting-edge reference book discusses the intervention of artificial intelligence in the fields of drug development, modified drug delivery systems, pharmaceutical technology, and medical devices development. This comprehensive book includes an overview of artificial intelligence in pharmaceutical sciences and applications in the drug discovery and development process. It discusses the role of machine learning in the automated detection and sorting of pharmaceutical formulations. It covers nanosafety and the role of artificial intelligence in predicting potential adverse biological effects. FEATURES Includes lucid, step-by-step instructions to apply artificial intelligence and machine learning in pharmaceutical sciences Explores the application of artificial intelligence in nanosafety and prediction of potential hazards Covers application of artificial intelligence in drug discovery and drug development Reviews the role of artificial intelligence in assessment of pharmaceutical formulations Provides artificial intelligence solutions for experts in the pharmaceutical and medical devices industries This book is meant for academicians, students, and industry experts in pharmaceutical sciences, medicine, and pharmacology.

Artificial Intelligence-based Healthcare Systems

Author : Manju,Sandeep Kumar,Sardar M. N. Islam
Publisher : Springer Nature
Page : 208 pages
File Size : 51,9 Mb
Release : 2023-12-02
Category : Computers
ISBN : 9783031419256

Get Book

Artificial Intelligence-based Healthcare Systems by Manju,Sandeep Kumar,Sardar M. N. Islam Pdf

This book explores new applications in the field of science and technology for healthcare systems. The main focus of this book is to devise smart, efficient and robust solutions for the health care sector to serve the major population of rural areas. Artificial Intelligence-based Healthcare Systems encourages scientists, engineers, and scholars across the multiple disciplines to design smart intelligent innovations on rural healthcare issues and motivate to collaborate multiple ideas to design best solutions. It also helps the readers at various levels of knowledge to further enhance their understanding for new tools and smart solutions.

Communication Design and Branding

Author : Nuno Martins,Daniel Raposo
Publisher : Springer Nature
Page : 362 pages
File Size : 52,9 Mb
Release : 2023-10-01
Category : Business & Economics
ISBN : 9783031353857

Get Book

Communication Design and Branding by Nuno Martins,Daniel Raposo Pdf

This book gathers new empirical findings fostering advances in the areas of communication design and branding, with a special emphasis of interdisciplinary approaches showing how to combine knowledge in those fields to improve businesses in a digital, global world. Gathering original, peer-reviewed contributions written by designers, computer scientists, marketer and product managers, this book provides both the communication and branding communities with a timely snapshot of current strategies and best-practices to improve different kinds of business through design. By highlighting current challenges, it is also intended to inspire and foster collaboration between different groups, in both university and industry.

Intelligent Data Analysis for Biomedical Applications

Author : Hemanth D. Jude,Deepak Gupta,Valentina Emilia Balas
Publisher : Academic Press
Page : 294 pages
File Size : 46,7 Mb
Release : 2019-03-15
Category : Computers
ISBN : 9780128156438

Get Book

Intelligent Data Analysis for Biomedical Applications by Hemanth D. Jude,Deepak Gupta,Valentina Emilia Balas Pdf

Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition, machine learning, data abstraction and visualization tools for the analysis of data and discovery of mechanisms that create data. It provides computational methods and tools for intelligent data analysis, with an emphasis on problem-solving relating to automated data collection, such as computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and more. This book provides useful references for educational institutions, industry professionals, researchers, scientists, engineers and practitioners interested in intelligent data analysis, knowledge discovery, and decision support in databases. Provides the methods and tools necessary for intelligent data analysis and gives solutions to problems resulting from automated data collection Contains an analysis of medical databases to provide diagnostic expert systems Addresses the integration of intelligent data analysis techniques within biomedical information systems

Intelligent Systems and Human Machine Collaboration

Author : Siddhartha Bhattacharyya,Mario Koeppen,Debashis De,Vincenzo Piuri
Publisher : Springer Nature
Page : 280 pages
File Size : 43,5 Mb
Release : 2023-03-29
Category : Computers
ISBN : 9789811984778

Get Book

Intelligent Systems and Human Machine Collaboration by Siddhartha Bhattacharyya,Mario Koeppen,Debashis De,Vincenzo Piuri Pdf

The book constitutes proceedings of the International Conference on Intelligent Systems and Human-Machine Collaboration 2022. The papers consist of research from different domains of human-machine interaction, computer engineering like quantum computational intelligence, big data analytics, the Internet of things, etc. The book includes significant contributions from academia and industry dealing with human-machine interaction both from the theoretical development and the application point of view. It also brings out research articles in interdisciplinary platforms applying human-machine interaction. The book is useful to researchers and practitioners alike.

Explainable Artificial Intelligence (XAI) in Healthcare

Author : Utku Kose,Nilgun Sengoz,Xi Chen,Jose Antonio Marmolejo Saucedo
Publisher : CRC Press
Page : 251 pages
File Size : 40,9 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 for Biomedical Data Analysis

Author : Mourad Elloumi
Publisher : Springer Nature
Page : 358 pages
File Size : 44,7 Mb
Release : 2021-07-13
Category : Medical
ISBN : 9783030716769

Get Book

Deep Learning for Biomedical Data Analysis by Mourad Elloumi Pdf

This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical information on these techniques, approaches and the related problems without overcrowding the reader's head. It presents the results of the latest investigations in the field of DL for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine fundamental theory of Artificial Intelligence (AI), Machine Learning (ML) and DL with practical applications in Biology and Medicine. Certainly, the list of topics covered in this book is not exhaustive but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis. The book finds a balance between theoretical and practical coverage of a wide range of issues in the field of biomedical data analysis, thanks to DL. The few published books on DL for biomedical data analysis either focus on specific topics or lack technical depth. The chapters presented in this book were selected for quality and relevance. The book also presents experiments that provide qualitative and quantitative overviews in the field of biomedical data analysis. The reader will require some familiarity with AI, ML and DL and will learn about techniques and approaches that deal with the most important and/or the newest topics encountered in the field of DL for biomedical data analysis. He/she will discover both the fundamentals behind DL techniques and approaches, and their applications on biomedical data. This book can also serve as a reference book for graduate courses in Bioinformatics, AI, ML and DL. The book aims not only at professional researchers and practitioners but also graduate students, senior undergraduate students and young researchers. This book will certainly show the way to new techniques and approaches to make new discoveries.

Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics

Author : Sunil Kumar Dhal,Subhendu Kumar Pani,Srinivas Prasad,Sudhir Kumar Mohapatra
Publisher : John Wiley & Sons
Page : 356 pages
File Size : 48,8 Mb
Release : 2022-06-28
Category : Computers
ISBN : 9781119791737

Get Book

Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics by Sunil Kumar Dhal,Subhendu Kumar Pani,Srinivas Prasad,Sudhir Kumar Mohapatra Pdf

BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.

Data Analytics in Biomedical Engineering and Healthcare

Author : Kun Chang Lee,Sanjiban Sekhar Roy,Pijush Samui,Vijay Kumar
Publisher : Academic Press
Page : 298 pages
File Size : 52,7 Mb
Release : 2020-10-18
Category : Science
ISBN : 9780128193150

Get Book

Data Analytics in Biomedical Engineering and Healthcare by Kun Chang Lee,Sanjiban Sekhar Roy,Pijush Samui,Vijay Kumar Pdf

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks. Examines the development and application of data analytics applications in biomedical data Presents innovative classification and regression models for predicting various diseases Discusses genome structure prediction using predictive modeling Shows readers how to develop clinical decision support systems Shows researchers and specialists how to use hybrid learning for better medical diagnosis, including case studies of healthcare applications using the MapReduce and Hadoop frameworks