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Data Science for Effective Healthcare Systems [Kõva köide]

Edited by (PIET), Edited by (JUIT), Edited by (JUIT), Edited by (JUIT)
  • Formaat: Hardback, 224 pages, kõrgus x laius: 254x178 mm, kaal: 570 g, 34 Tables, black and white; 69 Line drawings, black and white; 25 Halftones, black and white; 94 Illustrations, black and white
  • Sari: Chapman & Hall/CRC Internet of Things
  • Ilmumisaeg: 29-Jul-2022
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 1032105682
  • ISBN-13: 9781032105680
Teised raamatud teemal:
  • Formaat: Hardback, 224 pages, kõrgus x laius: 254x178 mm, kaal: 570 g, 34 Tables, black and white; 69 Line drawings, black and white; 25 Halftones, black and white; 94 Illustrations, black and white
  • Sari: Chapman & Hall/CRC Internet of Things
  • Ilmumisaeg: 29-Jul-2022
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 1032105682
  • ISBN-13: 9781032105680
Teised raamatud teemal:
"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. 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"--

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.



This book has a prime focus on the importance of data science in the healthcare domain. The aim of the book is to provide the future scope of these technologies in the health care domain. It will benefit research scholar, faculty, research organizations, and students to get insights into these emerging technologies in the healthcare domain.

Preface vii
Editors ix
1 Big Data in Healthcare: Applications and Challenges
1(14)
Monika
Pradeep Kumar
Sanjay Tyagi
2 Impact Analysis of COVID-19 on Different Countries: A Big Data Approach
15(10)
Reema Lalit
Nitin Sharma
3 Overview of Image Processing Technology in Healthcare Systems
25(12)
Ankit Singh
Sivanesan Dhandayuthapani
4 Artificial Intelligence to Fight against COVID-19 Coronavirus in Bharat
37(6)
Pushpendra Kumar Verma
Preety
5 Classification-Based Prediction Techniques Using ML: A Perspective for Health Care
43(14)
Meenakshi Malik
Aditi Kaushik
Rekha Khatana
6 Deep Learning for Drug Discovery: Challenges and Opportunities
57(12)
Aarti
7 Issues and Challenges Associated with Machine Learning Tools for Health Care System
69(10)
Parul Chhabra
Pradeep Kumar Bhatia
8 Real-Time Data Analysis of COVID-19 Vaccination Progress Over the World
79(10)
Bijan Paul
Aditi Roy
Khan Raqib Mahmud
Mohammad Rifat Rashid
9 Descriptive, Predictive, and Prescriptive Analytics in Healthcare
89(16)
Kalimullah Lone
Shabir Ahmad Sofi
10 IoT Enabled Worker Health, Safety Monitoring and Visual Data Analytics
105(12)
Selvaraj Kesavan
Subhash Almel
B.S. Muralidhar
11 Prevalence of Nomophobia and Its Association with Text Neck Syndrome and Insomnia in Young Adults during COVID-19
117(16)
Richa Hirendra Rai
Vishal Mehta
Pallavi
Sachindra Pratap Singh
12 The Role of AI, Fuzzy Logic System in Computational Biology and Bioinformatics
133(16)
A.H.M. Shahariar Parvez
Sadiq Iqbal
Subrato Bharati
Prajoy Podder
Pinto Kumar Paul
Aditya Khamparia
13 Analysis for Early Prediction of Diabetes in Healthcare Using Classification Techniques
149(12)
Navneet Verma
Sukhdip Singh
Devendra Prasad
14 Nomenclature of Machine Learning Algorithms and Their Applications
161(8)
Ritu Agganval
Suneet Kumar
15 Breast Cancer Prognosis Using Machine Learning Approaches
169(14)
Nadeem Yousuf Khanday
Shabir Ahmad Sofi
16 Machine Learning-Based Active Contour Approach for the Recognition of Brain Tumor Progression
183(16)
Amit Chopra
Dinesh C. Verma
Rajneesh Gujral
17 A Deep Neural Networks-Based Cost-Effective Framework for Diabetic Retinopathy Detection
199(14)
Pawan Kumar Upadhyay
Siddharth Batra
Sunny Dhama
Index 213
Hari Singh; Dinesh Chander Verma