Recent Advances in AI-enabled Automated Medical Diagnosis
CRC Press (Verlag)
978-1-032-00856-1 (ISBN)
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.
1. Enhancement of COVID-19 Diagnosis Using Machine Learning and Texture Analyses of Lung Imaging 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 3. Deep Learning-based Respiratory Anomaly and COVID Diagnosis Using Audio and CT Scan Imagery 4. COVID-19 Forecasting in India through Deep Learning Models 5. Deep Learning-based Techniques in Medical Imaging for COVID-19 Diagnosis: A Survey 6. Embedding Explainable Artificial Intelligence in Clinical Decision Support Systems: The Brain Age Prediction Case Study 7. Machine Learning-based Biological Ageing Estimation Technologies: A Survey 8. Review on Social Behavior Analysis of Laboratory Animals: From Methodologies to Applications 9. Acute Lymphoblastic Leukemia Diagnosis Using Genetic Algorithm and Enhanced Clustering-based Feature Selection 10. Artificial Intelligence-enabled Automated Medical Prediction and Diagnosis in Trauma Patients 11. DCGAN-based Facial Expression Synthesis for Emotion Well-being Monitoring with Feature Extraction and Cluster Grouping 12. A Hybrid-DE for Automatic Retinal Image-based Blood Vessel Segmentation 13. Artificial Intelligence for Accurate Detection and Analysis of Freezing of Gait in Parkinson’s Disease 14. Sparse Model Identification for Nonstationary and Nonlinear Neural Dynamics Based on Multiwavelet Basis Expansion 15. How Weather Conditions Affect the Spread of COVID-19: Findings of a Study Using Contrastive Learning and NARMAX Models 16. New Measurement of the Body Mass Index with Bioimpedance Using a Novel Interpretable Takagi-Sugeno Fuzzy NARX Predictive Model 17. Training Therapy with BCI-based Neurofeedback Systems for Motor Rehabilitation 18. A Modified Dynamic Time Warping (MDTW) and Innovative Average Non-self Match Distance (ANSD) Method for Anomaly Detection in ECG Recordings 19. An Investigation on ECG-based Cardiological Diagnosis via Deep Learning Models 20. EEG-based Deep Emotional Diagnosis: A Comparative Study 21. A Novel Motor Imagery EEG Classification Approach Based on Time-Frequency Analysis and Convolutional Neural Network 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
| Erscheinungsdatum | 06.09.2024 |
|---|---|
| Zusatzinfo | 86 Tables, black and white; 12 Line drawings, color; 101 Line drawings, black and white; 2 Halftones, color; 41 Halftones, black and white; 14 Illustrations, color; 142 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 684 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Studium ► 2. Studienabschnitt (Klinik) ► Anamnese / Körperliche Untersuchung | |
| ISBN-10 | 1-032-00856-3 / 1032008563 |
| ISBN-13 | 978-1-032-00856-1 / 9781032008561 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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