Sensor Data Analytics for Intelligent Healthcare Delivery
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Sensor Data Analytics for Intelligent Healthcare Delivery: (Advances in Digital Technologies for Smart Applications)

Sensor Data Analytics for Intelligent Healthcare Delivery: (Advances in Digital Technologies for Smart Applications)

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About the Book

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.

Table of Contents:
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.


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Product Details
  • ISBN-13: 9781040425428
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: Chapman and Hall
  • Language: English
  • ISBN-10: 1040425429
  • Publisher Date: 28 Oct 2025
  • Binding: Digital (delivered electronically)
  • Series Title: Advances in Digital Technologies for Smart Applications


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Sensor Data Analytics for Intelligent Healthcare Delivery: (Advances in Digital Technologies for Smart Applications)
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Sensor Data Analytics for Intelligent Healthcare Delivery: (Advances in Digital Technologies for Smart Applications)
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