Informatics And Machine Learning

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Computational Intelligence For Machine Learning And Healthcare Informatics

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Author : Rajshree Srivastava
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2020-06-22

Computational Intelligence For Machine Learning And Healthcare Informatics written by Rajshree Srivastava and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-22 with Computers categories.

This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.

Deep Learning Machine Learning And Iot In Biomedical And Health Informatics

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Author : Sujata Dash
language : en
Publisher: CRC Press
Release Date : 2022-02-10

Deep Learning Machine Learning And Iot In Biomedical And Health Informatics written by Sujata Dash and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-10 with Computers categories.

Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever. The aim of these techniques is to accept imprecision, uncertainties and approximations to get a rapid solution. However, recent advancements in representation of intelligent IoTsystems generate a more intelligent and robust system providing a human interpretable, low-cost, and approximate solution. Intelligent IoT systems have demonstrated great performance to a variety of areas including big data analytics, time series, biomedical and health informatics. This book will be very beneficial for the new researchers and practitioners working in the biomedical and healthcare fields to quickly know the best performing methods. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practice of such areas as medical image retrieval, brain image segmentation, among others. • Discusses deep learning, IoT, machine learning, and biomedical data analysis with broad coverage of basic scientific applications • Presents deep learning and the tremendous improvement in accuracy, robustness, and cross- language generalizability it has over conventional approaches • Discusses various techniques of IoT systems for healthcare data analytics • Provides state-of-the-art methods of deep learning, machine learning and IoT in biomedical and health informatics • Focuses more on the application of algorithms in various real life biomedical and engineering problems

Deep Learning Techniques For Biomedical And Health Informatics

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Author : Sujata Dash
language : en
Publisher: Springer Nature
Release Date : 2019-11-14

Deep Learning Techniques For Biomedical And Health Informatics written by Sujata Dash and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-14 with Technology & Engineering categories.

This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model. This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health. It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.

Machine Learning For Non Less Invasive Methods In Health Informatics

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Author : Kun Qian
language : en
Publisher: Frontiers Media SA
Release Date : 2021-11-26

Machine Learning For Non Less Invasive Methods In Health Informatics written by Kun Qian and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-26 with Medical categories.

Machine Learning For Health Informatics

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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2016-12-10

Machine Learning For Health Informatics written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-10 with Computers categories.

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.

Machine Learning And Iot Applications For Health Informatics

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Author : Pijush Samui
language : en
Publisher: CRC Press
Release Date : 2024-10-31

Machine Learning And Iot Applications For Health Informatics written by Pijush Samui and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-31 with Computers categories.

This book brings together leading experts from around the world to explore the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) in healthcare. It provides a platform for studying a future where healthcare becomes more precise, personalized, and accessible for all. The book covers recent advancements that will shape the future of healthcare and how artificial intelligence is revolutionizing disease detection, from analyzing chest X-rays for pneumonia to solving the secrets of our genes. It investigates the transformative potential of smart devices, real-time analysis of heart data, and personalized treatment plan creation. It shows how ML and IoT work and presents real-world examples of how they are leading to earlier and more accurate diagnoses and personalized treatments. Therefore, this edited book will be an invaluable resource for researchers, healthcare professionals, data scientists, or simply someone passionate about the future of healthcare. Readers will discover the exciting possibilities that lie ahead at the crossroads of ML, IoT, and health informatics.

Artificial Intelligence And Machine Learning In Health Care And Medical Sciences

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Author : Gyorgy J. Simon
language : en
Publisher: Springer Nature
Release Date : 2024-03-04

Artificial Intelligence And Machine Learning In Health Care And Medical Sciences written by Gyorgy J. Simon and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-04 with Medical categories.

This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Care is taken to systematically describe the concepts to facilitate the reader in developing a thorough conceptual understanding of how different methods and resulting models function and how these relate to their applicability to various issues in health care and medical sciences. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfallsis a comprehensive guide to how AI and ML techniques can best be applied in health care. The emphasis placed on how to avoid a variety of pitfalls that can be encountered makes it an indispensable guide for all medical informatics professionals and physicians who utilize these methodologies on a day-to-day basis. Furthermore, this work will be of significant interest to health data scientists, administrators and to students in the health sciences seeking an up-to-date resource on the topic.

Data Driven Analytics For Healthcare

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Author : Meghna Sharma
language : en
Publisher: CRC Press
Release Date : 2025-02-10

Data Driven Analytics For Healthcare written by Meghna Sharma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-10 with Computers categories.

The new book highlights the application of artificial intelligence, machine learning, and deep learning techniques to diagnose medical problems. General predictive analysis methods are explained in disease detection applications along with machine learning techniques for the implementation of predictive analysis methods. The book covers object detection approaches for diseases such as pneumonia, application of monitoring and tracking the coronavirus disease, various endodontic applications for handling diagnostic abnormalities using deep learning methods, applications of healthcare for human activity recognition, and more.

Healthcare Solutions Using Machine Learning And Informatics

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Author : Punit Gupta
language : en
Publisher: CRC Press
Release Date : 2022-10-21

Healthcare Solutions Using Machine Learning And Informatics written by Punit Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-21 with Medical categories.

Healthcare Solutions Using Machine Learning and Informatics covers novel and innovative solutions for healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artificial intelligence, machine learning, and intelligent IoT-based solutions for medical image analysis, medical big-data processing, and disease predictions. Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence. The wide variety of topics covered include: Artificial Intelligence in healthcare Machine learning solutions for such disease as diabetes, arthritis, cardiovascular disease, and COVID-19 Big data analytics solutions for healthcare data processing Reliable biomedical applications using AI models Intelligent IoT in healthcare The book explains fundamental concepts as well as the advanced use cases, illustrating how to apply emerging technologies such as machine learning, AI models, and data informatics into practice to tackle challenges in the field of healthcare with real-world scenarios. Chapters contributed by noted academicians and professionals examine various solutions, frameworks, applications, case studies, and best practices in the healthcare domain.

Machine Learning In Biomedical And Health Informatics

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Author : Sudip Kumar Sahana
language : en
Publisher: CRC Press
Release Date : 2025-09-23

Machine Learning In Biomedical And Health Informatics written by Sudip Kumar Sahana and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-23 with Technology & Engineering categories.

Machine learning is playing an indispensable role in framing clinical decisions and enhancing accuracy. This new book offers a comprehensive take on the field of biomedical and health informatics, discussing topics that include predictive health analytics, pandemic management, AI ethics, application and integration of Internet of Things and machine learning for effective healthcare, and more. The book covers a range of bioinformatics tools and methods and their relation to drug designing and drug screening using ML. Several chapters cover clustering techniques and other methods for analyzing human heart-related disorders. The authors also explore the use of ML in creating adaptive therapies for using chemotherapy and androgen deprivation therapy for prostate cancer and for tracking diseases such as Parkinson’s Speech, Covid-19, and others. Case studies are included that demonstrate the practical use of ML in healthcare informatics.