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E-raamat: Smart Healthcare Systems [Taylor & Francis e-raamat]

Edited by (JIIT, Noida), Edited by (JIIT, Noida)
  • Formaat: 248 pages, 28 Tables, black and white; 93 Line drawings, black and white; 31 Halftones, black and white; 124 Illustrations, black and white
  • Ilmumisaeg: 31-Jul-2019
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-13: 9780429020575
  • Taylor & Francis e-raamat
  • Hind: 207,73 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 296,75 €
  • Säästad 30%
  • Formaat: 248 pages, 28 Tables, black and white; 93 Line drawings, black and white; 31 Halftones, black and white; 124 Illustrations, black and white
  • Ilmumisaeg: 31-Jul-2019
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-13: 9780429020575
About the Book

The book provides details of applying intelligent mining techniques for extracting and pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing.

Salient Features of the Book











Exhaustive coverage of Data Analysis using R





Real-life healthcare models for:















Visually Impaired





Disease Diagnosis and Treatment options





Applications of Big Data and Deep Learning in Healthcare





Drug Discovery















Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications





Compare and analyze recent healthcare technologies and trends

Target Audience

This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.
Preface vii
Editors ix
Contributors xi
1 Big Data Analytics in Healthcare
1(16)
Priti Bhardwaj
Niyati Baliyan
2 Smart Medical Diagnosis
17(14)
Raghav Maheshwari
Amit Singh
Siddharth Agraxval
Adwitiya Sinha
3 Lifestyle Application for Visually Impaired
31(18)
Megha Rathi
Ananya Singhal
4 Classification of Genetic Mutations
49(20)
Megha Rathi
Ishant Tyagi
Jatin Shad
Shubham Sharma
Siddharth Gaur
5 m-Health: Community-Based Android Application for Medical Services
69(14)
Mahima Narang
Charu Nigam
Nisha Chaurasia
6 Nanoemulsions: Status in Antimicrobial Therapy
83(26)
Atinderpal Kaur
Rakhi Bansal
Sonal Gupta
Reema Gabrani
Shweta Dang
7 Analysis of Air Quality and Impacts on Human Health
109(16)
Japsehaj Singh Wahi
Mayank Deepak Thar
Muskan Garg
Charu Goyal
Megha Rathi
8 Brain Tumor Detection and Classification in MRI: Technique for Smart Healthcare Adaptation
125(10)
Asmita Dixit
Aparajita Nanda
9 Deep Strategies in Computer-Assisted Diagnosis and Classification of Abnormalities in Medical Images
135(16)
Ankit Vidyarthi
Shilpa Gundagatti
Nisha Chaurasia
10 Major Histocompatibility Complex Binding and Various Health Parameters Analysis
151(14)
Abhinav Gautam
Arjun Singh Chauhan
Ayush Srivastava
Chetan Jadon
Megha Rathi
11 Partial Digest Problem
165(14)
Urvi Agarwal
Sanchi Prakash
Harshit Agarwal
Prantik Biswas
Suma Dawn
Aparajita Nanda
12 Deep Learning for Next-Generation Healthcare: A Survey of State-of-the-Art and Research Prospects
179(20)
Ankita Verma
Deepti Singh
13 Applications of Protein Nanoparticles as Drug Delivery Vehicle
199(18)
Reema Gabrani
Ritu Ghildiyal
Neetigyata Pratap
Garima Sharma
Shweta Dang
14 Exploring Food Domain Using Deep Neural Networks
217(10)
Megha Rathi
Samyak Jain
Uday Aggarwal
Index 227
Dr. Adwitiya Sinha received her PhD from Jawaharlal Nehru University (JNU), New Delhi. She is a recipient of a Senior Research Fellowship from CSIR, New Delhi, India and a UGC Research Scholarship. Her application-based research is mainly focused on large-scale graphs, data analytics, and confluence of sensor-based applications with social networking.

Megha Rathi has 10 years of teaching experience. She has worked on the Xform generator research project of at NIC, Delhi. She has experience in software development and worked as a Project Associate at IIT Delhi. Her research areas include Data Mining, Data Science Analytics, Health Science, and Machine Learning.