Application of the artificial intelligence-rapid whole-genome sequencing diagnostic system in the neonatal/pediatric intensive care unit / 中国当代儿科杂志
Zhongguo dangdai erke zazhi
; Zhongguo dangdai erke zazhi;(12): 433-437, 2021.
Article
em Zh
| WPRIM
| ID: wpr-879872
Biblioteca responsável:
WPRO
ABSTRACT
Pediatric patients in the neonatal intensive care unit (NICU) and the pediatric intensive care unit (PICU) have a high incidence rate of genetic diseases, and early rapid etiological diagnosis and targeted interventions can help to reduce mortality or improve prognosis. Whole-genome sequencing covers more comprehensive information including point mutation, copy number, and structural and rearrangement variations in the intron region and has become one of the powerful diagnostic tools for genetic diseases. Sequencing data require highly professional judgment and interpretation and are returned for clinical application after several weeks, which cannot meet the need for the diagnosis and treatment of genetic diseases in children. This article introduces the clinical application of rapid whole-genome sequencing in the NICU/PICU and briefly describes related techniques of artificial intelligence-rapid whole-genome sequencing diagnostic system, a rapid high-throughput automated platform for the diagnosis of genetic diseases. The diagnostic system introduces artificial intelligence into the processing of data after whole-genome sequencing and can solve the problems of long time and professional interpretation required for routine genome sequencing and provide a rapid diagnostic regimen for critically ill children suspected of genetic diseases within 24 hours, and therefore, it holds promise for clinical application.
Texto completo:
1
Índice:
WPRIM
Assunto principal:
Inteligência Artificial
/
Unidades de Terapia Intensiva Pediátrica
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Unidades de Terapia Intensiva Neonatal
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Estado Terminal
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Sequenciamento Completo do Genoma
Tipo de estudo:
Diagnostic_studies
Limite:
Child
/
Humans
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Newborn
Idioma:
Zh
Revista:
Zhongguo dangdai erke zazhi
Ano de publicação:
2021
Tipo de documento:
Article