Machine Learning Models and Architectures for Biomedical Signal Processing

Machine Learning Models and Architectures for Biomedical Signal Processing

Tripathi, Suman Lata; Balas, Valentina Emilia; Mahmud, Mufti; Banerjee, Soumya

Elsevier Science Publishing Co Inc

11/2024

400

Mole

9780443221583

Pré-lançamento - envio 15 a 20 dias após a sua edição

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Section 1: Introduction to bioinformatics 1.1 Recent trends of bioinformatics 1.2 Biomedical signal processing technique 1.3 Transfer Learning based Arrhythmia classification using Electrocardiogram Section 2: Machine learning models for biomedical signal processing 2.1 Exploring Machine Learning Models for Biomedical Signal Processing: A Comprehensive Review 2.2 Machine Learning for Audio Processing: From Feature Extraction to Model Selection 2.3 Pre-processing of MRI images suitable for Artificial Intelligence-based Alzheimer's Disease classification 2.4 Machine Learning Models for Text and Image Processing 2.5 Assistive Technology for Neuro-rehabilitation Applications Using Machine Learning Techniques 2.6 Deep Learning Architectures in Computer Vision based Medical Imaging Applications with Emerging Challenges 2.7 Relevance of Artificial Intelligence, Machine Learning, and Biomedical Devices to Healthcare Quality and patient Outcomes 2.8 AI-Based ECG Signal processing applications 2.9 Deep Learning Approach for the Prediction of Skin Diseases Section 3: Brain computer interfaces (BCI) 3.1 Brain-Computer Interface 3.2 Analysis on Types of Brain-Computer Interfaces for Disabled Person 3.3 Brain Computer Interfaces for elderly and disabled person Section 4: Real time architecture design for biomedical signals 4.1 Machine learning model implementation with FPGA'S 4.2 Smart Biomedical Devices for Smart Healthcare 4.3 FPGA implementation for explainable machine learning and deep learning models to real time problems Section 5: Software and Hardware-based Applications for biomedical Informatics 5.1 Software Applications for Biometric Informatics 5.2 Smart Medical Devices: Making Health Care More Intelligent 5.3 Security modules for biomedical signal processing 5.4 Artificial intelligence-based diagnostic tool for cardiovascular risk prediction 5.5 Machine Learning Algorithm approach in risk prediction of Liver Cancer
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Machine learning models; Bioinformatics; Reconfigurable architectures; Field programmable gate array (FPGA); Computational intelligence; Brain-computer interfaces; Biomedical signal processing; Biomedical ASIC design; MATLAB; HDL