Advances of Machine Learning for Knowledge Mining in Electronic Health Records (eBook, ePUB)

Redaktion: Fathimal, P. Mohamed; T. I., Manish; Lakshmi, Venkataraman; Loret, J. B. Shajilin; Kumar, T. Ganesh

• Format: ePub

Produktbeschreibung

The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR, consisting of demographics, medical history, and diagnosis.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Erscheinungstermin: 7. März 2025
• Englisch
• ISBN-13: 9781040305744
• Artikelnr.: 73301833

Autorenporträt

P. Mohamed Fathimal is working as an Assistant Professor in the Department of Computer Science and Engineering, Anna University. She received her PhD, ME, and BE in Computer Science and Engineering from Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu. She has 21 years of teaching experience. Her research interests include Machine Learning, Digital Image Processing, and Information Security. She has published more than 20 papers and 1 patent. T. Ganesh Kumar works as an Associate Professor at the School of Computing Science and Engineering at Galgotias University, NCR, Delhi. He received an ME degree in Computer Science and Engineering from Manonmaniam Sundaranar University, Tamilnadu, India. He completed his full-time PhD degree in Computer Science and Engineering at Manonmaniam Sundaranar University. He was a Co-Investigator for two government of India-sponsored funded projects He has published many reputed international SCI and Scopus-indexed journals and conferences. He is a reviewer of many reputed journals. He has published more than 10 Indian patents. J. B Shajilin Loret is working as a Professor & Head in the Department of Information Technology at Francis Xavier Engineering College, Tirunelveli. She received her BTech degree in Information Technology from Anna University Chennai and her MTech degree from Manonmaniam Sundaranar University. She completed her Ph.D. in wireless networks at Anna University Chennai. Her area of interest includes Wireless networks, Network security. She has more than 15 years of teaching experience in engineering colleges. She has more than 30 publications in Reputed Journals. She also published 3 Indian patents and Author of book chapters also. Venkataraman Lakshmi graduated BE degree from IIT Roorkee, MS in Environmental Engineering from the University of Lowa, and a Ph.D. degree from Princeton University. He is currently a professor in the department of system engineering and environment. He has served as Cox Visiting professor at Stanford University. He has over 120 articles and 400 presentations. He is an associate editor and Editor-in-Chief in various journals. Manish.T.I work as a Professor in the Department of Computer Science and Engineering, SCMS School of Engineering and Technology. He received an ME degree in Computer Science and Engineering from Manonmaniam Sundaranar University, Tamilnadu, India. He completed his Ph.D. degree in Computer Science and Engineering at Manonmaniam Sundaranar University. He was a Co-Investigator for two government of India-sponsored funded projects He has published many reputed international SCI and Scopus indexed journals and conferences. He is a reviewer of many reputed journals. He has published Indian patents in India.

Inhaltsangabe

1. An Introduction to Electronic Health Records 2. Challenges and
Strategies for Extracting Secure Patterns by Using EHR 3. The Art of
Organizing EHR Data: A Classification Journey Through Structured,
Unstructured, and Semi-Structured Records 4. A blockchain Enabled Framework
for Electronic Health Records 5. Cardio Vascular Disease Diagnosis using
Deep Learning models 6. A Computational Analysis for the Diagnosis of
Schizophrenia Disease Using Machine Learning Methods 7. Predicting Lung
Cancer Using Supervised Algorithms:A Machine Learning Approach 8. Article
summarising the application of Artificial Intelligence and Machine Learning
Techniques to several forms of Electronic Health Records 9. Machine
Learning Techniques to Predict the Risk of Chronic Obstructive Pulmonary
Disease 10. Dynamic Learning Scheduling Algorithm and Multilayer Perceptron
Model for Heart Disease Prediction System 11. Efficient Heart Disease
Prediction using IBM Cloud Storage with Auto AI Service 12. Electronic
Health Records-A survey