Advances of Machine Learning for Knowledge Mining in Electronic Health Records

1. Auflage 2025
ISBN: 978-1-032-52610-2
Verlag: Chapman and Hall/CRC

Buch, Englisch, 284 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 596 g

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, with a focus on the design and representation of structured, semi-structured, and unstructured data.

- Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health records

- Covers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured data

- Discusses supervised and unsupervised learning in electronic health records

- Describes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health records

This book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning.

Zielgruppe

Academic, Professional Reference, and Undergraduate Advanced

Autoren/Hrsg.

Fathimal, P. Mohamed

Kumar, T. Ganesh

Loret, J. B. Shajilin

Lakshmi, Venkataraman

T. I., Manish

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Technische Informatik
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing

Inhaltsverzeichnis

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

Über Autor(innen)

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.