Machine learning models and architectures for biomedical signal processing /
Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates how efficient machine and deep learning models can support high-speed processors with reconfigur...
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| Format: | eBook |
| Language: | English |
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London, United Kingdom :
Academic Press,
[2025]
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| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Recent trends in biomedical informatics / Neha Singh, Shilpi Birla, and Neeraj Kumar Shukla
- Biomedical signal processing technique / Manoj Singh Adhikari, Manoj Sindhwani, and Shippu Sachdeva
- Transfer learning-based arrhythmia classification using electrocardiogram / Khuraijam Nelson Singh, Sinam Ajitkumar Singh, and Swanirbhar Majumder
- Exploring machine learning models for biomedical signal processing : A comprehensive review / Tarun Kumar Vashishth, Vikas Sharma, and Shahanawaj Ahamad
- Machine learning for audio processing : From feature extraction to model selection / Aditya Kumar and Jainath Yadav
- Enhancing insights : Unravelling the potential of preprocessing MRI for artificial intelligence based Alzheimer's disease classification / Vimbi Viswan, Faizal Hajamohideen, and Mufti Mahmud
- Machine learning models for text and image processing / Taiwo Soewu, Harpreet Kaur, and Suman Lata Tripathi
- Assistive technology for neuro-rehabilitation applications using machine learning techniques / Suman Lata Tripathi, Lakshmi Prasanna Dasari, and Mufti Mahmud
- Deep learning architectures in computer vision based medical imaging applications with emerging challenges / Sumit Kumar and Shallu Sharma
- Relevance of artificial intelligence, machine learning, and biomedical devices to healthcare quality and patient outcomes / Abhishek Kumar, Nasmin Jiwani, and Ankur Srivastava
- Artificial intelligence-based electrocardiogram signal processing applications / Thi Diem Tran and Ngoc Quoc Tran
- Deep learning approach for the prediction of skin diseases / Ritu Chauhan, Drishti Gogna, and Sandhya Avasthi
- Braincomputer interface / Shraddha Jain Shrama and Ratnalata Gupta
- Human-computer interface developments include systems that can decipher enhanced human language and contextual cues while interacting with digital devices / Harishchander Anandaram, M.S. Nidhya, and Benita Christopher
- Brain-computer interfaces for elderly and disabled persons / S. Niveditha, D. Shobana, and P.M. Yazhini
- Machine learning model implementation with FPGAs / Harsh Yellai, Sai Teja Kothapalli, and Shruti Bhargava Choubey
- Smart biomedical devices for smart healthcare / Wasswa Shafik
- FPGA implementation for explainable machine learning and deep learning models to real-time problems / Suman Lata Tripathi, Mufti Mahmud, and Valentina Emilia Balas
- Software applications for biometric informatics / Taskeen Zaidi and Saurav Mallik
- Smart medical devices : Making healthcare more intelligent / M. Menagadevi, Nirmala Madian, and Remya Rajendran
- Security modules for biomedical signal processing using Internet of Things / Monika Parmar, Shaminder Kaur, and Shilpi Birla
- Artificial intelligence-based diagnostic tools for cardiovascular risk prediction / Shivaswamy Sharmila, Nirmala Madian, and Remya Rajendran
- Machine learning algorithm approach in risk prediction of liver cancer / Ritu Chauhan, Akanksha Sahi, and Sandhya Avasthi.