راهنمای هوش مصنوعی در مهندسی پزشکی

"Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques, such as machine learning, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume explores how artificial intelligence (AI) can be applied to these expert systems by mimicking the human expert's knowledge in order to predict and monitor the health status in real time. The accuracy of the AI systems is drastically increasing by using machine learning, digitized medical data acquisition, wireless medical data communication, and computing infrastructure AI approaches, helping to solve complex issues in the biomedical industry and playing a vital role in future healthcare applications. The volume takes a multidisciplinary perspective of employing these new applications in biomedical engineering, exploring the combination of engineering principles with biological knowledge that contributes to the development of revolutionary and life-saving concepts. Topics include: Security and privacy issues in biomedical AI systems and potential solutions, healthcare applications using biomedical AI systems, machine learning in biomedical engineering, live patient monitoring systems, semantic annotation of healthcare data. This book presents a broad exploration of biomedical systems using artificial intelligence techniques with detailed coverage of the applications, techniques, algorithms, platforms, and tools in biomedical AI systems. This book will benefit researchers, medical and industry practitioners, academicians, and students."-- Provided by publisher Cover Half Title Title Page Copyright Page Series Page About the Editors Contents Contributors Abbreviations Preface 1. Design of Medical Expert Systems Using Machine Learning Techniques 2. From Design Issues to Validation: Machine Learning in Biomedical Engineering 3. Biomedical Engineering and Informatics Using Artificial Intelligence 4. Hybrid Genetic Algorithms for Biomedical Applications 5. Healthcare Applications of the Biomedical AI System 6. Applications of Artificial Intelligence in Biomedical Engineering 7. Biomedical Imaging Techniques Using AI Systems 8. Analysis of Heart Disease Prediction Using Machine Learning Techniques 9. A Review on Patient Monitoring and Diagnosis Assistance by Artificial Intelligence Tools 10. Semantic Annotation of Healthcare Data 11. Drug Side Effect Frequency Mining over a Large Twitter Dataset using Apache Spark 12. Deep Learning in Brain Segmentation 13. Security and Privacy Issues in Biomedical AI Systems and Potential Solutions 14. LiMoS—Live Patient Monitoring System 15. Real-Time Detection of Facial Expressions Using k-NN, SVM, Ensemble classifier and Convolution Neural Networks 16. Analysis and Interpretation of Uterine Contraction Signals Using Artificial Intelligence 17. Enhanced Classification Performance of Cardiotocogram Data for Fetal State Anticipation Using Evolutionary Feature Reduction Techniques 18. Deployment of Supervised Machine Learning and Deep Learning Algorithms in Biomedical Text Classification 19. Energy Efficient Optimum Cluster Head Estimation for Body Area Networks 20. Segmentation and Classification of Tumour Regions from Brain Magnetic Resonance Images by Neural Network-Based Technique 21. A Hypothetical Study in Biomedical Based Artificial Intelligence Systems using Machine Language (ML) Rudiments 22. Neural Source Connectivity Estimation using particle filter and Granger causality methods 23. Exploration of Lymph Node-Negative Breast Cancers by Support Vector Machines, Naïve Bayes, and Decision Trees: A Comparative Study Index