| Description |
1 online resource |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Summary |
Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. 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® -- $$c Provided by publisher. |
| Note |
Description based on online resource; title from digital title page (viewed on April 14, 2022). |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Chapter 1. Biomedical engineering and the evolution of artificial intelligence -- Chapter 2. Introduction to Cognitive Science, Cognitive Computing, and Human Cognitive relation to help in the solution of Artificial Intelligence Biomedical Engineering problems -- Chapter 3. Artificial Intelligence Models Applied to Biomedical Engineering -- Chapter 4. Machine Learning Models Applied to Biomedical Engineering -- Chapter 5. Deep Learning Models Principles Applied to Biomedical Engineering -- Chapter 6. Deep Learning Models Evolution Applied to Biomedical Engineering -- Chapter 7. Cognitive learning and reasoning models applied to biomedical engineering. |
| Subject |
Biomedical engineering -- Computer simulation.
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Artificial intelligence -- Medical applications.
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Artificial intelligence -- Biological applications.
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Cognitive science.
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Nervous system -- Diseases -- Pathophysiology -- Data processing.
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Nervous system -- Diseases -- Data processing.
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Génie biomédical -- Simulation par ordinateur.
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Intelligence artificielle en médecine.
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Intelligence artificielle -- Applications biologiques.
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Sciences cognitives.
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Système nerveux -- Maladies -- Informatique.
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Artificial intelligence -- Biological applications
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Artificial intelligence -- Medical applications
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Biomedical engineering -- Computer simulation
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Cognitive science
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| Other Form: |
Print version: Garza-Ulloa, Jorge. Applied biomedical engineering using artificial intelligence and cognitive models 0128207183 9780128207185 (OCoLC)1231959921 |
| ISBN |
9780128209349 (electronic bk.) |
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0128209348 (electronic bk.) |
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9780128207185 |
| Standard No. |
AU@ 000070477185 |
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