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: September 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.
  1. Introduction and Tour of Various Tools of Predictive Analytics for Medical Science
  2. Machine Learning Classification Algorithms for Prediction of Diseases
  3. Biomedical Data Visualization and Data Representation
  4. Classification and Clustering Algorithms for Medical Data
  5. Optimized Data Retrieval and Data Storage for Health Care Application
  6. Computational Intelligence System for Healthcare
  7. High Performance Intelligent Systems for Real Time Medical Imaging
  8. A Real-time Patient Health Monitoring System
  9. Ensembled Convolutional Neural Network for Multi-class Skin Cancer Detection
  10. Similarity Index Retrieval for School Kids' Sitting Posture Identification
  11. Identification, Analysis and Recommendation of Sitting Posture of School Kids.
  12. Fatty Liver Disease Prediction: Using Machine Learning Algorithms
  13. Computer Aided Drug Design Case Study on Development of New Chemical Entities in the Management of HIV
  14. Detection of Brain Tumor MRI Images using Comparison using Comprises on Analysis of Deep Learning Techniques
  15. Biomedical Applications of Footprint Recognition: Harnessing Artificial Intelligence and Machine Learning for Footprint Image Monitoring