This book explores the transformative potential of sensor data analytics in healthcare, focusing on both real-time and streaming analytics applications in clinical and non-clinical environments. It introduces the foundations of sensor data collection and analytics, delving into data acquisition techniques, mining challenges, and the integration of wearable technologies. The book addresses key methodologies and real-world use cases, illustrating how sensor data can improve healthcare delivery, optimise operations, and enhance patient outcomes. It includes topics from algorithmic approaches to practical implementations across a variety of medical domains.
- Covers fundamental concepts of sensor data acquisition, preprocessing, and real-time analysis for healthcare systems.
- Examines the role of wearables in continuous monitoring and their analytics use in clinical workflows.
- Addresses the challenges and techniques for handling streaming data in dynamic healthcare environments.
- Explores machine learning and data mining algorithms tailored to healthcare sensor data.
- Provides examples across hospital operations, patient monitoring, diagnostics, and healthcare management.
This book is for researchers and practitioners in data science, healthcare informatics, biomedical engineering, and healthcare management.
This book explores the healthcare applications of sensor data analytics and also focuses on real-time and streaming analytics in healthcare. Covering sensor data analytics fundamentals, the book explores sensor data collection and data analysis applications. It also discusses healthcare applications of wearable devices.
Chapter
1. Healthcare Sensor Data Analytics: Foundational Concepts,
Architecture, Data Analysis Techniques, Data Quality, Errors, and
Applications.
Chapter
2. Statistical Approximation of Streaming Sensor Data
for Enhancing Healthcare Analytics.
Chapter
3. Sensor Data Analytics for
Transformative Healthcare Solutions A Comprehensive Insights.
Chapter
4.
Healthcare Sensor Data Analysis for Real-Time Anomaly Detection: A
Comprehensive Insights.
Chapter
5. Basic Concepts and Principles of
Healthcare Sensor Data Analytics.
Chapter
6. Design and Development of
Physiotherapy Robot to Aid Medical Practitioners for Human Upper-limb
Rehabilitation.
Chapter
7. Mortality Prediction in Non-Alcoholic Fatty Liver
Disease using Machine Learning.
Chapter
8. Predicting Cognitive Impairment
through Handwriting Analysis: A Machine Learning Framework for Enhanced
Clinical Decision-Making.
Chapter
9. Optimizing Deep Learning for Pneumonia
Diagnosis using Chest X-Ray Data.
Chapter
10. Melanoma Detection Using Deep
Convolutional Neural Networks: A High-Resolution Image-Based Approach.
Chapter
11. Advanced Skin Cancer Classification Using Xception Deep Learning
Architecture using Dermoscopic Images.
Chapter
12. Neuro-Fuzzy Multimodal
Ensemble Algorithm for Alzheimer's Disease Prediction.
Chapter
13. Optimizing
Bidirectional Encoder Representations from Transformers for Medical
Healthcare: Unveiling Insights from Fine-Tuning for Efficient Question
Answering with Gen AI.
Chapter
14. Utilizing Cosine Wavelet Geometric Guided
Sparse Representation Transform for Lossless Medical Image Compression to
Enhance Image Quality.
Chapter
15. A Comprehensive Analysis on Advanced
Techniques in Healthcare Sensor Data Analytics.
Chapter
16. Internet of
Medical Things in Healthcare: Enhancing Patient Care and Monitoring through
Connected Devices.
G.S.Karthick is currently working as an Assistant Professor in the Department of Software Systems, PSG College of Arts & Science, Coimbatore, India. Previously, he worked as a Research Fellow under the DST-ICPS Project from April 2019 to March 2022 in the Department of Computer Science, School of Computer Science and Engineering, Bharathiar University, Coimbatore, India. Also, he worked as an Assistant Professor in the Department of Computer Science, Sri Ramakrishna College of Arts and Science, Coimbatore, India. He received his Ph.D. in Computer Science from Bharathiar University (University Department) in February 2023. He topped the Post-Graduation with Gold Medal in 2017 from Bharathiar University, Coimbatore, India. He topped Under-Graduation with an exemplary performance from SNR Sons College, Coimbatore, India, and also aced three subjects to receive gold medals in 2015. He has qualified UGC-NET Computer Science and Applications in December 2020. Further, he has visited many institutions and universities as a resource person at various events. He has received an Indian Patent Grant for his innovative contribution to the field of Wireless Networks and the Internet of Things. He has published research papers in international journals and presented papers at International and National Conferences. He has published many book chapters and in addition, he has edited four books and authored two books. He is an Associate Editor of IJHISI, IJITN and IJEHMC. Also, he is an active reviewer in high-standard journals and many peer-reviewed journals. He has received many awards and rewards for his achievements in academic and research careers. His areas of specialization are Machine Learning, the Internet of Things, Wireless Sensor Networks, and Analysis of Algorithms. His current research interests focus on the recent developments in the healthcare internet of things and machine learning algorithms.
Lisainfo e-raamatute kohta