Poonam Tanwar – författare

Big data is a field of research that is growing rapidly, and as the Covid-19 crisis has shown, health care is an area that could benefit greatly from its increased use and application. Big data, as derived partly from the internet of things and analysed according to specific algorithms, has a large and beneficial role to play in preventative medicine, in monitoring the health of specific groups, and in improving diagnostics.Big Data Analytics and Intelligence: A Perspective for Health Care focuses on various areas of health care, ranging from nutrition to cancer, and providing diverse perspectives on all of them. This book explores the entire life-cycle of big data, from information retrieval to analysis, and it shows how big data’s applications can enhance, streamline and improve services for patients and health-care professionals. Each chapter focuses on a specific area of health care and how big data is applicable to it, with background and current examples provided.

This book uncovers stakes and possibilities offered by Computational Intelligence and Predictive Analytics to Medical Science. The main focus is on data technologies,classification, analysis and mining, information retrieval, and in the algorithms needed to elaborate the informations. A section with use cases and applications follows the two main parts of the book, respectively dedicated to the foundations and techniques of the discipline.

In this book, we embark on a journey into the realm of predictive data modeling for biomedical data and imaging in healthcare. It explores the potential of predictive analytics in the field of medical science through utilizing various tools and techniques to unravel insights and enhance patient care. This volume creates a medium for an interchange of knowledge from expertise and concerns in the field of predictive data modeling. In detail, the research work on this will include the effective use of predictive data modeling algorithms to run image analysis tasks for understanding.Predictive Data Modelling for Biomedical Data and Imaging is divided into three sections, namely Section I – Beginning of Predictive Data Modeling for Biomedical Data and Imaging/Healthcare, Section II – Data Design and Analysis for Biomedical Data and Imaging/Healthcare, and Section III – Case Studies of Predictive Analytics for Biomedical Data and Imaging/Healthcare. We hope this book will inspire further research and innovation in the field of predictive data modeling for biomedical data and imaging in healthcare. By exploring diverse case studies and methodologies, this book contributes to the advancement of healthcare practices, ultimately improving patient outcomes and well-being.