Description
Developments in deep learning in the past decade have led to phenomenal growth in AI-based automated medical diagnosis, opening a door to a new era of both medical research and medical industry. It is a golden age for researchers involved in the development and application of advanced machine learning techniques for medical and clinical problems. This book captures the most recent important advances in this cross-disciplinary topic and brings the latest advances to a wide audience including experts, researchers, students, industry developers and medical services.
Table of Contents
1. Enhancement of COVID-19 Diagnosis Using Machine Learning and Texture Analyses of Lung Imaging
Bhuvan Mittal, JungHwan Oh
2. Modeling COVID-19 Pandemic Dynamics Using Transparent, Interpretable, Parsimonious and Simulatable (TIPS) Machine Learning Models: A Case Study from Systems Thinking and System Identification Perspectives
Hua-Liang Wei, Stephen A. Billings
3. Deep Learning-based Respiratory Anomaly and COVID Diagnosis Using Audio and CT Scan Imagery
Conor Wall, Chengyu Liu and Li Zhang
4. COVID-19 Forecasting in India through Deep Learning Models
Arindam Chaudhuri and Soumya K. Ghosh
5. Deep Learning-based Techniques in Medical Imaging for COVID-19 Diagnosis: A Survey
Fozia Mehboob, Abdul Rauf, Khalid M. Malik, Richard Jiang, Abdul K.J. Saudagar, Abdullah AlTameem and Mohammed AlKhathami
6. Embedding Explainable Artificial Intelligence in Clinical Decision Support Systems: The Brain Age Prediction Case Study
Angela Lombardi, Domenico Diacono, Nicola Amoroso, Alfonso Monaco, Sabina Tangaro and Roberto Bellotti
7. Machine Learning-based Biological Ageing Estimation Technologies: A Survey
Zhaonian Zhang, Richard Jiang, Danny Crookes and Paul Chazot
8. Review on Social Behavior Analysis of Laboratory Animals: From Methodologies to Applications
Ziping Jiang, Paul L. Chazot and Richard Jiang
9. Acute Lymphoblastic Leukemia Diagnosis Using Genetic Algorithm and Enhanced Clustering-based Feature Selection
Siew Chin Neoh, Srisukkham Worawut, Li Zhang and Md. Mostafa Kamal Sarker
10. Artificial Intelligence-enabled Automated Medical Prediction and Diagnosis in Trauma Patients
Lianyong Li, Changqing Zhong, Gang Wang, Wei Wu, Yuzhu Guo, Zheng Zhang, Bo Yang, Xiaotong Lou, Ke Li and Heming Yang
11. DCGAN-based Facial Expression Synthesis for Emotion Well-being Monitoring with Feature Extraction and Cluster Grouping
Eaby Kollonoor Babu, Kamlesh Mistry and Li Zhang
12. A Hybrid-DE for Automatic Retinal Image-based Blood Vessel Segmentation
Colin Paul Joy, Kamlesh Mistry, Gobind Pillai and Li Zhang
13. Artificial Intelligence for Accurate Detection and Analysis of Freezing of Gait in Parkinson’s Disease
Wenting Yang, Simeng Li, Debin Huang, Hantao Li, Lipeng Wang, Wei Zhang and Yuzhu Guo
14. Sparse Model Identification for Nonstationary and Nonlinear Neural Dynamics Based on Multiwavelet Basis Expansion
Song Xu, Lina Wang and Jingjing Liu
15. How Weather Conditions Affect the Spread of COVID-19: Findings of a Study Using Contrastive Learning and NARMAX Models
Yiming Sun and Hua-Liang Wei
16. New Measurement of the Body Mass Index with Bioimpedance Using a Novel Interpretable Takagi-Sugeno Fuzzy NARX Predictive Model
Changjiang He, Yuanlin Gu, Hua-Liang Wei and Qinggang Meng
17. Training Therapy with BCI-based Neurofeedback Systems for Motor Rehabilitation
Jingjing Luo, Qiying Chen, Hongbo Wang, Youhao Wang and Qiang Du
18. A Modified Dynamic Time Warping (MDTW) and Innovative Average Non-self Match Distance (ANSD) Method for Anomaly Detection in ECG Recordings
Xinxin Yao and Hua-Liang Wei
19. An Investigation on ECG-based Cardiological Diagnosis via Deep Learning Models
Alex Meehan, Zhaonian Zhang, Bryan Williams and Richard Jiang
20. EEG-based Deep Emotional Diagnosis: A Comparative Study
Geyi Liu, Zhaonian Zhang, Richard Jiang, Danny Crookes and Paul Chazot
21. A Novel Motor Imagery EEG Classification Approach Based on Time-Frequency Analysis and Convolutional Neural Network
Qinghua Wang, Lina Wang and Song Xu
22. Classification of EEG Signals for Brain-Computer Interfaces using a Bayesian-Fuzzy Extreme Learning Machine
Adrian Rubio-Solis, Carlos Beltran-Perez and Hua-Liang Wei
