Predictive Intelligence in Biomedical and Health Informatics

Predictive Intelligence in Biomedical and Health Informatics
Author: Rajshree Srivastava
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 180
Release: 2020-10-12
Genre: Computers
ISBN: 3110676125
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Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.

Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics

Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics
Author: Sunil Kumar Dhal
Publisher: John Wiley & Sons
Total Pages: 356
Release: 2022-05-20
Genre: Computers
ISBN: 1119792355
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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.

Smart Computational Intelligence in Biomedical and Health Informatics

Smart Computational Intelligence in Biomedical and Health Informatics
Author: Amit Kumar Manocha
Publisher: CRC Press
Total Pages: 203
Release: 2021-09-27
Genre: Computers
ISBN: 1000434370
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Smart Computational Intelligence in Biomedical and Health Informatics presents state-of-the-art innovations; research, design, and implementation of methodological and algorithmic solutions to data processing problems, including analysis of evolving trends in health informatics and computer-aided diagnosis. This book describes practical, applications-led research regarding the use of methods and devices in clinical diagnosis, disease prevention, and patient monitoring and management. It also covers simulation and modeling, measurement and control, analysis, information extraction and monitoring of physiological data in clinical medicine and the biological sciences. FEATURES Covers evolutionary approaches to solve optimization problems in biomedical engineering Discusses IoT, Cloud computing, and data analytics in healthcare informatics Provides computational intelligence-based solution for diagnosis of diseases Reviews modelling and simulations in designing of biomedical equipment Promotes machine learning-based approaches to improvements in biomedical engineering problems This book is for researchers, graduate students in healthcare, biomedical engineers, and those interested in health informatics, computational intelligence, and machine learning.

Advanced Computational Intelligence in Healthcare-7

Advanced Computational Intelligence in Healthcare-7
Author: Ilias Maglogiannis
Publisher: Springer Nature
Total Pages: 169
Release: 2020-03-23
Genre: Technology & Engineering
ISBN: 3662611147
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This book presents state-of-the-art works and systematic reviews in the emerging field of computational intelligence (CI) in electronic health care. The respective chapters present surveys and practical examples of artificial intelligence applications in the areas of Human-Machine Interface (HMI) and affective computing, machine learning, big health data and visualization analytics, computer vision and medical image analysis. The book also addresses new and emerging topics in CI for health care such as the utilization of Social Media (SM) and the introduction of new intelligent paradigms in the security and privacy domains, which are critical for the health sector. The chapters, while of course not exhaustively addressing all the possible aspects of the aforementioned areas, are indicative of the dynamic nature of interdisciplinary research being pursued. Accordingly, the book is intended not only for researchers in the respective fields, but also for medical and administrative personnel working in the health sector, as well as managers and stakeholders responsible for making strategic decisions and defining public health policies.

Artificial Intelligence for Innovative Healthcare Informatics

Artificial Intelligence for Innovative Healthcare Informatics
Author: Shabir Ahmad Parah
Publisher: Springer Nature
Total Pages: 320
Release: 2022-05-23
Genre: Medical
ISBN: 3030965694
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There are several popular books published in Healthcare Computational Informatics like Computational Bioengineering and Bioinformatics (2020), Springer; Health Informatics (2017), Springer; Health Informatics Vision: From Data via Information to Knowledge (2019), IOS Press; Data Analytics in Biomedical Engineering and Healthcare (2020), Elsevier. However, in all these mentioned books, the challenges in Biomedical Imaging are solved in one dimension by use of any specific technology like Image Processing, Machine Learning or Computer Aided Systems. In this book, the book it has been attempted to bring all technologies related to computational analytics together and apply them on Biomedical Imaging.

Machine Learning for Health Informatics

Machine Learning for Health Informatics
Author: Andreas Holzinger
Publisher: Springer
Total Pages: 0
Release: 2016-12-10
Genre: Computers
ISBN: 9783319504773
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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.

Computational Intelligence and Blockchain in Biomedical and Health Informatics

Computational Intelligence and Blockchain in Biomedical and Health Informatics
Author: Pankaj Bhambri
Publisher: CRC Press
Total Pages: 361
Release: 2024-06-19
Genre: Computers
ISBN: 1040044093
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Advancements in computational intelligence, which encompasses artificial intelligence, machine learning, and data analytics, have revolutionized the way we process and analyze biomedical and health data. These techniques offer novel approaches to understanding complex biological systems, improving disease diagnosis, optimizing treatment plans, and enhancing patient outcomes. Computational Intelligence and Blockchain in Biomedical and Health Informatics introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields and provides a framework and summary of the various methods. The book emphasizes the role of advanced computational techniques and offers demonstrative examples throughout. Techniques to analyze the impacts on the biomedical and health Informatics domains are discussed along with major challenges in deployment. Rounding out the book are highlights of the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability along with two case studies. This book is highly beneficial to educators, researchers, and anyone involved with health data. Features: • Introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields. • Provides a framework and a summary of various computational intelligence and blockchain methods. • Emphasizes the role of advanced computational techniques and offers demonstrative examples throughout. • Techniques to analyze the impact on biomedical and health informatics are discussed along with major challenges in deployment. • Highlights the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability.

Biomedical Data Mining for Information Retrieval

Biomedical Data Mining for Information Retrieval
Author: Sujata Dash
Publisher: John Wiley & Sons
Total Pages: 450
Release: 2021-08-06
Genre: Computers
ISBN: 1119711266
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BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.

Deep Learning in Biomedical and Health Informatics

Deep Learning in Biomedical and Health Informatics
Author: M. A. Jabbar
Publisher: CRC Press
Total Pages: 224
Release: 2021-09-26
Genre: Computers
ISBN: 1000429083
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This book provides a proficient guide on the relationship between Artificial Intelligence (AI) and healthcare and how AI is changing all aspects of the healthcare industry. It also covers how deep learning will help in diagnosis and the prediction of disease spread. The editors present a comprehensive review of research applying deep learning in health informatics in the fields of medical imaging, electronic health records, genomics, and sensing, and highlights various challenges in applying deep learning in health care. This book also includes applications and case studies across all areas of AI in healthcare data. The editors also aim to provide new theories, techniques, developments, and applications of deep learning, and to solve emerging problems in healthcare and other domains. This book is intended for computer scientists, biomedical engineers, and healthcare professionals researching and developing deep learning techniques. In short, the volume : Discusses the relationship between AI and healthcare, and how AI is changing the health care industry. Considers uses of deep learning in diagnosis and prediction of disease spread. Presents a comprehensive review of research applying deep learning in health informatics across multiple fields. Highlights challenges in applying deep learning in the field. Promotes research in ddeep llearning application in understanding the biomedical process. Dr.. M.A. Jabbar is a professor and Head of the Department AI&ML, Vardhaman College of Engineering, Hyderabad, Telangana, India. Prof. (Dr.) Ajith Abraham is the Director of Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA. Dr.. Onur Dogan is an assistant professor at İzmir Bakırçay University, Turkey. Prof. Dr. Ana Madureira is the Director of The Interdisciplinary Studies Research Center at Instituto Superior de Engenharia do Porto (ISEP), Portugal. Dr.. Sanju Tiwari is a senior researcher at Universidad Autonoma de Tamaulipas, Mexico.