Applied biomedical engineering using artificial intelligence and cognitive models:
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...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London, UK ; San Diego, CA
Academic Press
[2021]
|
| Schlagworte: | |
| Online-Zugang: | FAB01 |
| Zusammenfassung: | 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 -- |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 9780128209349 0128209348 |
Internformat
MARC
| LEADER | 00000nmm a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV049407145 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 231113s2021 |||| o||u| ||||||eng d | ||
| 020 | |a 9780128209349 |9 9780128209349 | ||
| 020 | |a 0128209348 |9 0128209348 | ||
| 035 | |a (OCoLC)1410701003 | ||
| 035 | |a (DE-599)BVBBV049407145 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-1043 | ||
| 100 | 1 | |a Garza-Ulloa, Jorge |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Applied biomedical engineering using artificial intelligence and cognitive models |c Jorge Garza-Ulloa |
| 264 | 1 | |a London, UK ; San Diego, CA |b Academic Press |c [2021] | |
| 300 | |a 1 Online-Ressource | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 505 | 8 | |a 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 | |
| 520 | 3 | |a 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 -- | |
| 653 | 0 | |a Biomedical engineering / Computer simulation | |
| 653 | 0 | |a Artificial intelligence / Medical applications | |
| 653 | 0 | |a Artificial intelligence / Biological applications | |
| 653 | 0 | |a Cognitive science | |
| 653 | 0 | |a Nervous system / Diseases / Pathophysiology / Data processing | |
| 653 | 0 | |a Nervous system / Diseases / Data processing | |
| 653 | 0 | |a Génie biomédical / Simulation par ordinateur | |
| 653 | 0 | |a Intelligence artificielle en médecine | |
| 653 | 0 | |a Intelligence artificielle / Applications biologiques | |
| 653 | 0 | |a Sciences cognitives | |
| 653 | 0 | |a Système nerveux / Maladies / Informatique | |
| 653 | 0 | |a Artificial intelligence / Biological applications | |
| 653 | 0 | |a Artificial intelligence / Medical applications | |
| 653 | 0 | |a Biomedical engineering / Computer simulation | |
| 653 | 0 | |a Cognitive science | |
| 776 | 0 | 8 | |i Print version |n Druck-Ausgabe |z 0128207183 |a Garza-Ulloa, Jorge |t Applied biomedical engineering using artificial intelligence and cognitive models |z 9780128207185 |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 0128209348 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |
| 912 | |a ZDB-30-PQE | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-034734263 | ||
| 966 | e | |u https://ebookcentral.proquest.com/lib/th-ab/detail.action?docID=6819959 |l FAB01 |p ZDB-30-PQE |x Aggregator |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804186130415878144 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Garza-Ulloa, Jorge |
| author_facet | Garza-Ulloa, Jorge |
| author_role | aut |
| author_sort | Garza-Ulloa, Jorge |
| author_variant | j g u jgu |
| building | Verbundindex |
| bvnumber | BV049407145 |
| collection | ZDB-30-PQE |
| 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 |
| ctrlnum | (OCoLC)1410701003 (DE-599)BVBBV049407145 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04655nmm a2200529 c 4500</leader><controlfield tag="001">BV049407145</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">231113s2021 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780128209349</subfield><subfield code="9">9780128209349</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">0128209348</subfield><subfield code="9">0128209348</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1410701003</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV049407145</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-1043</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Garza-Ulloa, Jorge</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Applied biomedical engineering using artificial intelligence and cognitive models</subfield><subfield code="c">Jorge Garza-Ulloa</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">London, UK ; San Diego, CA</subfield><subfield code="b">Academic Press</subfield><subfield code="c">[2021]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">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 --</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Biomedical engineering / Computer simulation</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Artificial intelligence / Medical applications</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Artificial intelligence / Biological applications</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Cognitive science</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Nervous system / Diseases / Pathophysiology / Data processing</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Nervous system / Diseases / Data processing</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Génie biomédical / Simulation par ordinateur</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Intelligence artificielle en médecine</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Intelligence artificielle / Applications biologiques</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Sciences cognitives</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Système nerveux / Maladies / Informatique</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Artificial intelligence / Biological applications</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Artificial intelligence / Medical applications</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Biomedical engineering / Computer simulation</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Cognitive science</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">0128207183</subfield><subfield code="a">Garza-Ulloa, Jorge</subfield><subfield code="t">Applied biomedical engineering using artificial intelligence and cognitive models</subfield><subfield code="z">9780128207185</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe</subfield><subfield code="z">0128209348</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034734263</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/th-ab/detail.action?docID=6819959</subfield><subfield code="l">FAB01</subfield><subfield code="p">ZDB-30-PQE</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV049407145 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:05:19Z |
| indexdate | 2024-07-10T10:06:14Z |
| institution | BVB |
| isbn | 9780128209349 0128209348 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034734263 |
| oclc_num | 1410701003 |
| open_access_boolean | |
| owner | DE-1043 |
| owner_facet | DE-1043 |
| physical | 1 Online-Ressource |
| psigel | ZDB-30-PQE |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | Academic Press |
| record_format | marc |
| spelling | Garza-Ulloa, Jorge Verfasser aut Applied biomedical engineering using artificial intelligence and cognitive models Jorge Garza-Ulloa London, UK ; San Diego, CA Academic Press [2021] 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier 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 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 -- Biomedical engineering / Computer simulation Artificial intelligence / Medical applications Artificial intelligence / Biological applications Cognitive science Nervous system / Diseases / Pathophysiology / Data processing Nervous system / Diseases / Data processing Génie biomédical / Simulation par ordinateur Intelligence artificielle en médecine Intelligence artificielle / Applications biologiques Sciences cognitives Système nerveux / Maladies / Informatique Print version Druck-Ausgabe 0128207183 Garza-Ulloa, Jorge Applied biomedical engineering using artificial intelligence and cognitive models 9780128207185 Erscheint auch als Online-Ausgabe 0128209348 Erscheint auch als Druck-Ausgabe |
| spellingShingle | Garza-Ulloa, Jorge Applied biomedical engineering using artificial intelligence and cognitive models 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 |
| title | Applied biomedical engineering using artificial intelligence and cognitive models |
| title_auth | Applied biomedical engineering using artificial intelligence and cognitive models |
| title_exact_search | Applied biomedical engineering using artificial intelligence and cognitive models |
| title_exact_search_txtP | Applied biomedical engineering using artificial intelligence and cognitive models |
| title_full | Applied biomedical engineering using artificial intelligence and cognitive models Jorge Garza-Ulloa |
| title_fullStr | Applied biomedical engineering using artificial intelligence and cognitive models Jorge Garza-Ulloa |
| title_full_unstemmed | Applied biomedical engineering using artificial intelligence and cognitive models Jorge Garza-Ulloa |
| title_short | Applied biomedical engineering using artificial intelligence and cognitive models |
| title_sort | applied biomedical engineering using artificial intelligence and cognitive models |
| work_keys_str_mv | AT garzaulloajorge appliedbiomedicalengineeringusingartificialintelligenceandcognitivemodels |