Analysis of Medical Modalities for Improved Diagnosis in Modern Healthcare

ISBN-13: 9780367705367 / Angielski / Twarda / 2021 / 324 str.

Varun Bajaj; G. R. Sinha

Opis

This book emphasizes the real-time challenges in medical modalities for variety of applications for analysis, classification and identification of different states for improvement of healthcare systems. Each chapter starts with the introduction, need and motivation of the medical modality and covers applications, alongwith real-time case studies.

Spis treści

1. Classification of Alertness and Drowsiness States using the Complex Wavelet Transform based Approach for EEG Records1.1Introduction1.2Methodology1.3Results and Discussion1.4Conclusion2. Stochastic Event Synchrony based on a Modified Sparse Bump Modeling: Application to PTSD EEG Signals2.1Introduction2.2Sparse Bump Modeling2.3Stochastic Event Synchrony2.4Synchro-squeezed wavelet transform2.5Stochastic event synchrony based on a modified bump modelling2.6Data description and preprocessing2.7Results2.8Conclusion3. HealFavor: A Chatbot Application in Healthcare3.1Introduction3.2Theoretical Background3.3Data Preparation Methodology3.4Prototype System Architecture3.5Machine Translation3.6Evaluation3.7Conclusion3.8Future Works4. Diagnosis of Neuromuscular Disorders using Machine Learning Techniques4.1Introduction4.2Literature Review4.3EMG Signal Classification Framework4.4Results and Discussion4.5Conclusion 5. Prosthesis control using undersampled surface electromyographic signals5.1Introduction5.2Myoelectric controlled prosthesis 5.3sEMG signal recording in myoelectric prosthesis control5.4Conclusion and future scope6. Title of chapter:Assessment and Diagnostic Methods for Coronavirus Disease 2019 (COVID-19) 6.1Introduction6.2Clinical findings of COVID-196.3Existing diagnostic tools6.4Current Screening tools for COVID-196.5Capnogram features6.6"Proposed tools for early screening of COVID-19 using respired CO2 features"6.7Conclusion7. Predictive Analysis of Breast Cancer using Infrared Images with Machine Learning Algorithms 7.1Introduction7.2Methods & Materials 7.3Classification using Machine Learning Models 7.4Performance Evaluation Parameters7.5Classification Results & Analysis7.6Conclusion & Future Work 8. Histopathological Image Analysis and Classification Techniques for Breast Cancer Detection8.1Introduction8.2Methodology8.3 Image Database8.4Performance Evaluation of CAD system8.5Results and Discussion8.6 Conclusion9. STUDY OF EMOTIONAL INTELLIGENCE & NEURO-FUZZY SYSTEM9.1Emotional Intelligence 9.2Emotions and Cognitive Intelligent Systems (CIS)9.3 Methods for Implementation of Emotional Intelligence 9.4Artificial Neural Network and Fuzzy Inference System9.5The Integrated Neuro Fuzzy Approach9.6 SUMMARY 10. ESSENTIAL STATISTICAL TOOLS FOR ANALYSIS OF BRAIN COMPUTER INTERFACE10.1 Introduction to testing of hypothesis10.2 Design of experiment10.3 Completely Randomized Design10.4 Randomized Block Design10.5 Latin Square Design10.6Factorial Experiment11. Brain Computer Interfaces: The basics, state of the art and future 11.1Introduction11.2Signal acquisition techniques for BCI11.3BCI types and brain signal patterns11.4Signal processing11.5Software tools for BCI11.6Conclusion and future perspectives12. Oriented Approaches for Brain Computing and Human Behavior Computing Using Machine Learning 12.1Overview of Machine Learning (Definition Approaches)12.2Machine Learning Algorithm for Brain Computing12.3Machine Learning Algorithms for Human Behavior Computing 13. An Automated Diagnosis System for Cardiac Arrhythmia Classification13.1Introduction13.2The Human Heart13.3Different Segments of ECG13.4Database13.5proposed Methodology13.6Experimental Results13.7Conclusion