Buch, Englisch, 704 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 1880 g
Buch, Englisch, 704 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 1880 g
ISBN: 978-0-12-820718-5
Verlag: William Andrew Publishing
The interaction between these three areas are studied in this book with the objective of obtaining AI models on injuries and neurologic diseases of the human body, studying diseases of the brain, spine and the nerves that connect them with the musculoskeletal system. There are more than 600 diseases of the nervous system, including brain tumors, epilepsy, Parkinson's disease, stroke, and many others. These diseases affect the human cognitive system that sends orders from the central nervous system (CNS) through the peripheral nervous systems (PNS) to do tasks using the musculoskeletal system. These actions can be detected by many Bioinstruments (Biomedical Instruments) and cognitive device data, allowing us to apply AI using Machine Learning-Deep Learning-Cognitive Computing models through algorithms to analyze, detect, classify, and forecast the process of various illnesses, diseases, and injuries of the human body.
Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models provides readers with the study of injuries, illness, and neurological diseases of the human body through Artificial Intelligence using Machine Learning (ML), Deep Learning (DL) and Cognitive Computing (CC) models based on algorithms developed with MATLAB® and IBM Watson®.
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie
Weitere Infos & Material
1. Biomedical Engineering and the evolution of Artificial Intelligence 2. Introduction to Cognitive science, cognitive computing and human cognitive relation to help in the solution of AI Biomedical engineering problems 3. Artificial Intelligence models applied to Biomedical Engineering 4. Machine learning models applied to Biomedical Engineering 5. Deep learning models applied to Biomedical Engineering 6. Cognitive Computing models applied to Biomedical Engineering 7. C AI-ML-DL-CC models applied to Biomedical Engineering