Intelligent Information Retrieval for Healthcare Systems


Ankur Choudhary, PhD
Arun Prakash Agrawal, PhD
Parma Nand, PhD
Vishal Jain, PhD

Series: Internet of Things and Machine Learning
BISAC: TEC017000; MED003000

Ontology–based information extraction is considered as an effective method to improve the performance of information extraction (IE) systems. For research and disbursal of customized healthcare services, a major challenge is to efficiently retrieve and analyze the individual patient data from a large volume of heterogeneous data over a long span of time. This requires effective ontology-based information retrieval approaches for clinical information systems. This book is an attempt to highlight the key advances in ontology-based information retrieval techniques especially in the healthcare domain. The varied chapters attempt to uncover the current challenges in the application of ontology-based information retrieval techniques to the healthcare systems. This book is the first of its kind that highlights the ontology-driven information retrieval mechanisms and techniques being applied to healthcare as well as clinical information systems. It can serve as a textbook for courses in healthcare systems. It can also serve as a reference book to medical practitioners and researchers involved in implementing as well as providing customized health care solutions to patients.

Table of Contents


Chapter 1. Ontology-Based Information Retrieval System Using Blockchain for Reducing Cost of Customized Healthcare System
(S. Porkodi and D. Kesavaraja – Department of Computer Science and Engineering, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur, Tamilnadu, India)

Chapter 2. Ontological Multi-Agent System for Pandemic Zone Classification and Automated Policy Formation
(Gaurav Kant Shankhdhar, Himanshu Pandey, M. Darbari, Anurag Tiwari, and Bhaskar Karn – Department of Mathematics and Computer Science, Babu Banarasi Das University, Lucknow, India, et al.)

Chapter 3. An Overview of Ontology-Based Artificial Intelligence Services in Health Care Systems
(R. S. M. Lakshmi Patibandla, B. Tarakeswara Rao, V. Lakshman Narayana and V. Sesha Srinivas – Vignan’s Foundation for Science, Technology, and Research, Andhra Pradesh, India, et al.)

Chapter 4. DLCDI: A Novel Deep Learning Mechanism for Chronic Diseases Identification
(Pokkuluri Kiran Sree and Usha Devi N – Department of CSE, Shri Vishnu Engineering College for Women (A), Bhimavaram, Andhra, Pradesh, India, et al.)

Chapter 5. Novel Approach to Health Monitoring System
(Amrit Muskan, Kanishka, Karan Malhotra, Nishi Kumari, Manisha Rajoriya and Usha Tiwari – Department of Electrical Electronics and Communication Engineering School of Engineering and Technology, Sharda University, Greater Noida UP, India)

Chapter 6. IoT in Healthcare – Applications, Benefits, Challenges, Real-Time Uses, and Cases
(Gaddam Prathik Kumar, Kanishka Negi, Huzaif Muataq Naikoo, Subrata Sahana, and Sanjoy Das – School of Engineering and Technology, Sharda University, Greater Noida, Uttar Pradesh, India, et al.)

Chapter 7. Data Privacy and Security in Healthcare
(Ruby Jain, Ayush Kumar Singh, and Sanskruti Rajore – Symbiosis Skills and Professional University, Pune, India)

Chapter 8. Examining the Effect of Ashes of Vedic Homa and Its Scientific Impacts on AQI with Social Perspectives: An ML and CPS Based Experimental Study for Delhi-NCR Zone amidst Pandemic Threats
(Rohit Rastogi, Sheelu Sagar, Neeti Tandon, and T. Rajeshwari – Sr. Asst. Professor, Department of CSE, ABES Engineering College Ghaziabad, Ghaziabad, India, et al.)

Chapter 9. NLP: Smart Texting System Based on Android
(Frankly Chauhan, Jatin Kumar, Chandan Sahu, Subrata Sahana and Anil Kumar Sagar – Department of Computer Science and Engineering, Sharda University, Greater Noida, India)

Chapter 10. Storing and Maintaining the Smart Healthcare in IoT Environment
(N. Ambika – Department of Computer Applications, Sivananda Sarma Memorial RV College, Bangalore, India)


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