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Machine learning and data analytics for predicting, managing, and monitoring disease / Manikant Roy and Lovi Raj Gupta, editors. — 1 online resource — <URL:http://elib.fa.ru/ebsco/2997345.pdf>.

Record create date: 6/21/2021

Subject: Epidemiology — Data processing.; Epidemics — Mathematical models.; Machine learning.; Artificial intelligence — Medical applications.; Epidemiologic Methods; Artificial intelligence — Medical applications.; Epidemics — Mathematical models.; Epidemiology — Data processing.; Machine learning.

Collections: EBSCO

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"This book provides the recent various theoretical frameworks, empirical research and application of advanced analytics methods for disease detection, pandemic management, disease prediction etc. using the data analysis methods and their usages for taking timely decisions for prevention of such spread of pandemic and how people in government, society and administer can use these insights for overall management"--.

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Table of Contents

  • Cover
  • Title Page
  • Copyright Page
  • Book Series
  • Editorial Advisory Board
  • Table of Contents
  • Detailed Table of Contents
  • Preface
  • Acknowledgment
  • Chapter 1: Prediction of Neurological Disorders Using Visual Saliency
  • Chapter 2: An Exploratory Analysis and Predictive SIR Model for the Early Onset of COVID-19 in Tamil Nadu, India
  • Chapter 3: Predicting Daily Confirmed COVID-19 Cases in India
  • Chapter 4: A Study on COVID-19 Prediction and Detection With Artificial Intelligence-Based Real-Time Healthcare Monitoring Systems
  • Chapter 5: Landmark Recognition Using Ensemble-Based Machine Learning Models
  • Chapter 6: Image Classification Using Deep Neural Networks
  • Chapter 7: Pandemic Management Using Artificial Intelligence-Based Safety Measures
  • Chapter 8: Text Mining and Natural Language Processing for Health Informatics
  • Chapter 9: Plant Disease Detection Using Machine Learning Approaches
  • Chapter 10: Image Pre-Processing and Paddy Pests Detection Using Tensorflow
  • Chapter 11: Deep Learning Models for Detection and Diagnosis of Alzheimer's Disease
  • Chapter 12: Data Analytics to Predict, Detect, and Monitor Chronic Autoimmune Diseases Using Machine Learning Algorithms
  • Chapter 13: Criticality of E-Privacy and Data Leakage Amid the Pandemic
  • Chapter 14: Designing a Real-Time Dashboard for Pandemic Management
  • Chapter 15: Corona
  • Compilation of References
  • About the Contributors
  • Index

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