Data Science for Effective Healthcare Systems
1st Edition
Published on 29. July 2022
224 pages
978-1-000-61885-3 (ISBN)
Description
Data Science for Effective Healthcare Systems has a prime focus on the importance of data science in the healthcare domain. Various applications of data science in the health care domain have been studied to find possible solutions. In this period of COVID-19 pandemic data science and allied areas plays a vital role to deal with various aspect of health care. Image processing, detection & prevention from COVID-19 virus, drug discovery, early prediction, and prevention of diseases are some thrust areas where data science has proven to be indispensable.
Key Features:
The book offers comprehensive coverage of the most essential topics, including:
Big Data Analytics, Applications & Challenges in Healthcare
Descriptive, Predictive and Prescriptive Analytics in Healthcare
Artificial Intelligence, Machine Learning, Deep Learning and IoT in Healthcare
Data Science in Covid-19, Diabetes, Coronary Heart Diseases, Breast Cancer, Brain Tumor
The aim of this book is also to provide the future scope of these technologies in the health care domain. Last but not the least, this book will surely benefit research scholar, persons associated with healthcare, faculty, research organizations, and students to get insights into these emerging technologies in the healthcare domain.
Key Features:
The book offers comprehensive coverage of the most essential topics, including:
Big Data Analytics, Applications & Challenges in Healthcare
Descriptive, Predictive and Prescriptive Analytics in Healthcare
Artificial Intelligence, Machine Learning, Deep Learning and IoT in Healthcare
Data Science in Covid-19, Diabetes, Coronary Heart Diseases, Breast Cancer, Brain Tumor
The aim of this book is also to provide the future scope of these technologies in the health care domain. Last but not the least, this book will surely benefit research scholar, persons associated with healthcare, faculty, research organizations, and students to get insights into these emerging technologies in the healthcare domain.
More details
Series
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Product notice
Reflowable
Illustrations
34 Tables, black and white; 69 Line drawings, black and white; 25 Halftones, black and white; 94 Illustrations, black and white
ISBN-13
978-1-000-61885-3 (9781000618853)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Hari Singh | Ravindara Bhatt | Prateek Thakral
Data Science for Effective Healthcare Systems
Book
10/2024
1st Edition
Chapman & Hall/CRC
€65.50
Shipment within 10-20 days
Hari Singh | Ravindara Bhatt | Prateek Thakral
Data Science for Effective Healthcare Systems
Book
07/2022
1st Edition
Chapman & Hall/CRC
€147.30
Shipment within 10-20 days
Persons
Content
1. Big Data in Healthcare: Applications and Challenges. 2. Impact Analysis of COVID-19 on Different Countries: A Big Data Approach. 3. Overview of Image Processing Technology in Healthcare Systems. 4. Artificial Intelligence Fight Against the Covid-19 Coronavirus in Bharat. 5. Classification Based Prediction Techniques Using ML: A Perspective for Health Care. 6. Deep Learning for Drug Discovery: Challenges and Opportunities. 7. Issues and Challenges Associated with Machine Learning Tools for Health Care System. 8. Real-Time Data Analysis on Covid-19 Vaccination Progress over the World. 9. Descriptive, Predictive, and Prescriptive Analytics in Healthcare. 10. IoT Enabled Worker Health, Safety Monitoring and Visual Data Analytics. 11. Prevalence of Nomophobia and Its Association with Text Neck Syndrome and Insomnia in Young Adults during COVID-19. 12. The Role of AI, Fuzzy Logic System in Computational Biology and Bioinformatics. 13. Analysis for Early Prediction of Diabetes in Healthcare using Classification Techniques. 14. Nomenclature of Machine learning Algorithms and Its Applications. 15. Breast Cancer Prognosis using Machine Learning Approaches. 16. Machine Learning-Based Active Contour Approach for the Recognition of Brain Tumor Progression. 17. A Deep Neural Networks-Based Cost-Effective Framework for Diabetic Retinopathy Detection.
