Machine Learning for Brain Disorders
This Open Access volume provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts. Part One presents the fundamentals of ML. Part Two looks at the ma...
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| 格式: | Online |
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| 語言: | 英语 |
| 出版: |
Springer Nature
2023
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| 主題: | |
| 在線閱讀: | ONIX_20230814_9781071631959_4 |
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| _version_ | 1869524336533045248 |
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| collection | Directory of Open Access Books |
| description | This Open Access volume provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts. Part One presents the fundamentals of ML. Part Two looks at the main types of data used to characterize brain disorders, including clinical assessments, neuroimaging, electro- and magnetoencephalography, genetics and omics data, electronic health records, mobile devices, connected objects and sensors. Part Three covers the core methodologies of ML in brain disorders and the latest techniques used to study them. Part Four is dedicated to validation and datasets, and Part Five discusses applications of ML to various neurological and psychiatric disorders. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory. Comprehensive and cutting, Machine Learning for Brain Disorders is a valuable resource for researchers and graduate students who are new to this field, as well as experienced researchers who would like to further expand their knowledge in this area. This book will be useful to students and researchers from various backgrounds such as engineers, computer scientists, neurologists, psychiatrists, radiologists, and neuroscientists. |
| format | Online |
| id | doab-20.500.12854ir-112846 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1128462025-07-17T10:00:05Z Machine Learning for Brain Disorders Colliot, Olivier machine learning deep learning brain disorders neurology psychiatry data science neural networks statistical learning neuroimaging clinical data biomarkers omics electronic health records mobile devices thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences This Open Access volume provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts. Part One presents the fundamentals of ML. Part Two looks at the main types of data used to characterize brain disorders, including clinical assessments, neuroimaging, electro- and magnetoencephalography, genetics and omics data, electronic health records, mobile devices, connected objects and sensors. Part Three covers the core methodologies of ML in brain disorders and the latest techniques used to study them. Part Four is dedicated to validation and datasets, and Part Five discusses applications of ML to various neurological and psychiatric disorders. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory. Comprehensive and cutting, Machine Learning for Brain Disorders is a valuable resource for researchers and graduate students who are new to this field, as well as experienced researchers who would like to further expand their knowledge in this area. This book will be useful to students and researchers from various backgrounds such as engineers, computer scientists, neurologists, psychiatrists, radiologists, and neuroscientists. 2023-08-17T04:32:09Z 2023-08-17T04:32:09Z 2023-08-14T15:53:46Z 2023 book ONIX_20230814_9781071631959_4 OCN: 1391989569 https://library.oapen.org/handle/20.500.12657/75361 9781071631959 9781071631942 https://directory.doabooks.org/handle/20.500.12854/112846 eng Neuromethods open access image/png image/jpeg image/jpeg n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/75361/1/978-1-0716-3195-9.pdf https://library.oapen.org/bitstream/20.500.12657/75361/1/978-1-0716-3195-9.pdf https://library.oapen.org/bitstream/20.500.12657/75361/1/978-1-0716-3195-9.pdf Springer Nature Humana 10.1007/978-1-0716-3195-9 10.1007/978-1-0716-3195-9 9fa3421d-f917-4153-b9ab-fc337c396b5a 2fb2c9e0-22c2-42b4-8b47-176d1d2e09f9 9781071631959 9781071631942 Humana 1047 New York [...] open access |
| spellingShingle | machine learning deep learning brain disorders neurology psychiatry data science neural networks statistical learning neuroimaging clinical data biomarkers omics electronic health records mobile devices thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences Machine Learning for Brain Disorders |
| title | Machine Learning for Brain Disorders |
| title_full | Machine Learning for Brain Disorders |
| title_fullStr | Machine Learning for Brain Disorders |
| title_full_unstemmed | Machine Learning for Brain Disorders |
| title_short | Machine Learning for Brain Disorders |
| title_sort | machine learning for brain disorders |
| topic | machine learning deep learning brain disorders neurology psychiatry data science neural networks statistical learning neuroimaging clinical data biomarkers omics electronic health records mobile devices thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences |
| topic_facet | machine learning deep learning brain disorders neurology psychiatry data science neural networks statistical learning neuroimaging clinical data biomarkers omics electronic health records mobile devices thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences |
| url | ONIX_20230814_9781071631959_4 |