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Deep learning for brain disorders: from data processing to disease treatment.
Burgos, Ninon; Bottani, Simona; Faouzi, Johann; Thibeau-Sutre, Elina; Colliot, Olivier.
Afiliación
  • Burgos N; Paris Brain Institute, in the ARAMIS Lab.
  • Bottani S; Paris Brain Institute, in the ARAMIS Lab.
  • Faouzi J; Paris Brain Institute, in the ARAMIS Lab.
  • Thibeau-Sutre E; Paris Brain Institute, in the ARAMIS Lab.
  • Colliot O; ARAMIS Lab.
Brief Bioinform ; 22(2): 1560-1576, 2021 03 22.
Article en En | MEDLINE | ID: mdl-33316030
In order to reach precision medicine and improve patients' quality of life, machine learning is increasingly used in medicine. Brain disorders are often complex and heterogeneous, and several modalities such as demographic, clinical, imaging, genetics and environmental data have been studied to improve their understanding. Deep learning, a subpart of machine learning, provides complex algorithms that can learn from such various data. It has become state of the art in numerous fields, including computer vision and natural language processing, and is also growingly applied in medicine. In this article, we review the use of deep learning for brain disorders. More specifically, we identify the main applications, the concerned disorders and the types of architectures and data used. Finally, we provide guidelines to bridge the gap between research studies and clinical routine.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Encefalopatías / Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Encefalopatías / Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article