Full Description
The aim of this book is to present new computational techniques and methodologies for the analysis of the clinical, epidemiological and public health aspects of SARS-CoV-2 and COVID-19 pandemic. The book presents the use of soft computing techniques such as machine learning algorithms for analysis of the epidemiological aspects of the SARS-CoV-2. This book clearly explains novel computational image processing algorithms for the detection of COVID-19 lesions in lung CT and X-ray images. It explores various computational methods for computerized analysis of the SARS-CoV-2 infection including severity assessment. The book provides a detailed description of the algorithms which can potentially aid in mass screening of SARS-CoV-2 infected cases. Finally the book also explains the conventional epidemiological models and machine learning techniques for the prediction of the course of the COVID-19 epidemic. It also provides real life examples through case studies. The book is intended for biomedical engineers, mathematicians, postgraduate students; researchers; medical scientists working on identifying and tracking infectious diseases.
Contents
1. Artificial Intelligence Based CoVID-19 Detection using Medical Imaging Methods: A Review. 2. Review on Imaging Features for COVID-19. 3. Investigation of COVID-19 Chest X-ray Images using Texture Features -A Comprehensive Approach. 4. Efficient Diagnosis using Chest CT in COVID-19: A Review. 5. Automatic Mask Detection and Social Distance Alerting Based on a Deep Learning Computer Vision Algorithm. 6. Review of Effective Mathematical Modelling of Coronavirus Epidemic and Effect of Drone Disinfection. 7. ANFIS Algorithm based Modeling and Forecasting of the COVID-19 Epidemic: A Case Study in Tamil Nadu, India. 8. Prediction and Analysis of SARS-CoV-2 (COVID-19) Epidemic in India using LSTM Network
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