Predictive Data Modelling for Biomedical Data and Imaging

Predictive Data Modelling for Biomedical Data and Imaging

River Publishers Series in Biotechnology and Medical Research

Predictive Data Modelling for Biomedical Data and Imaging Forthcoming

Editors:
Poonam Tanwar, Department of Computer Science & Engineering, Manav Rachna International Institute of Research & Studies, Faridabad, India
Tapas Kumar, Department of Computer Science & Engineering, Manav Rachna International Institute of Research & Studies, Faridabad, India
K. Kalaiselvi, Department of Computer Applications, Vels Institute of Science, Technology and Advanced Studies, Chennai, India
Haider Raza, School of Computer Science and Electronics Engineering, University of Essex United Kingdom
Seema Rawat, Amity School of Engineering and Technology, Amity University, India.

ISBN: 9788770040778 e-ISBN: 9788770040761

Available: June 2024


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.
Predictive data modeling, machine learning, deep learning , convolution neural network, medical image processing, biomedical data, computational intelligence.