Decision Sciences in Bioinformatics
Theory and Practice
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Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 17 March 2026
- ISBN 9781032535494
- Binding Hardback
- No. of pages206 pages
- Size 234x156 mm
- Language English
- Illustrations 68 Illustrations, black & white; 68 Line drawings, black & white; 25 Tables, black & white 700
Categories
Short description:
Bioinformatics deals with computational and mathematical approaches for understanding and processing biological data.
MoreLong description:
Bioinformatics deals with computational and mathematical approaches for understanding and processing biological data. This book highlights the computational procedures and the applications evolving around biological data, including usage of decision sciences for a variety of applications, namely text mining, "OMIC" sciences, systems biology, analyzing biological/medical images, computer-aided diagnosis/treatment of diseases, decision sciences for public health with COVID-19 data, biodiversity, smart wearables, personalized medicine, data deluge issues, and knowledge management.
Key Features:
- Presents exclusive material on decision sciences in bioinformatics
- Highlights the computational procedures and applications evolving around biological data
- Provides solutions to problems in bioinformatics with decision sciences
- Addresses the research gaps in bioinformatics
- Includes case studies emphasizing societal needs
This book is aimed at researchers and graduate students in bioinformatics and data analytics.
MoreTable of Contents:
1. Semantic Data Fabric for Automated Health Care Data Integration Using AI for Risk Prognosis and Preventive Care; 2. Design of Implantable and Wearable Fractal Antenna for COVID-19 Health Monitoring Devices; 3. Thyroid Prediction Using Hybrid CNN and LSTM Model; 4. Hybrid GAN Model with LSTM-Combined ResNet Discriminator for COVID-19 Classification in CT Images; 5. Dynamic Weighted Ensemble Framework; 6. Cataloging of Alzheimer’s Disease and Its Stages Using Machine Learning; 7. COVID-19 Fake News Detection to Combat and Mitigate Its Spread; 8. Overcoming and Solving the Challenges of Data Deluge in Healthcare; 9. Utilizing Artificial Intelligence for the Identification of Plant Species and Detection of Diseases through Deep Learning
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