Optimizing Data Science Techniques for COVID-19 Detection, Mitigation, and Elimination

By Utku Kose, “Data Science for COVID-19” presents cutting-edge research on data science techniques for the detection, mitigation, treatment, and elimination of COVID-19. This comprehensive guide covers a wide range of data science applications concerning COVID-19 research, including image analysis, geoprocessing, predictive systems, design cognition, mobile technology, and telemedicine solutions.

Divided into sections, the book begins with an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. It then delves into artificial intelligence-based solutions, innovative treatment methods, and public safety measures. Finally, readers will learn about applications of big data and new data models for mitigation.

This book serves as a valuable resource for COVID-19 researchers and clinicians worldwide, providing insights into innovative data-oriented modeling and predictive techniques. It includes real-world feedback and user experiences from physicians and medical staff from around the world on the effectiveness of applied data science solutions.

Published by Elsevier Science on May 20, 2021, “Data Science for COVID-19” is available in English. The ISBNs for this publication are 9780128245361 and 9780128245378.

For researchers, clinicians, and data scientists interested in leveraging data science techniques to combat COVID-19, “Data Science for COVID-19” is an essential read. It offers a comprehensive overview of the latest research and applications in the field, making it a valuable addition to any medical or data science library.