Prediction Model of Amyotrophic Lateral Sclerosis by Deep Learning with Patient Induced Pluripotent Stem Cells.
Ann Neurol
; 89(6): 1226-1233, 2021 06.
Article
em En
| MEDLINE
| ID: mdl-33565152
ABSTRACT
In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence-based prediction model of ALS using induced pluripotent stem cells (iPSCs). Images of spinal motor neurons derived from healthy control subject and ALS patient iPSCs were analyzed by a convolutional neural network, and the algorithm achieved an area under the curve of 0.97 for classifying healthy control and ALS. This prediction model by deep learning algorithm with iPSC technology could support the diagnosis and may provide proactive treatment of ALS through future prospective research. ANN NEUROL 2021;891226-1233.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Diagnóstico Precoce
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Células-Tronco Pluripotentes Induzidas
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Aprendizado Profundo
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Esclerose Lateral Amiotrófica
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Neurônios Motores
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
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Risk_factors_studies
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Screening_studies
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Ann Neurol
Ano de publicação:
2021
Tipo de documento:
Article