Deep learning-based quantitative analyses of spontaneous movements and their association with early neurological development in preterm infants

This study aimed to develop quantitative assessments of spontaneous movements in high-risk preterm infants based on a deep learning algorithm. Video images of spontaneous movements were recorded in very preterm infants at the term-equivalent age. The Hammersmith Infant Neurological Examination (HINE...

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Detalles Bibliográficos
Autores principales: Shin, Hyun Iee, Shin, Hyung-Ik, Bang, Moon Suk, Kim, Don-Kyu, Shin, Seung Han, Kim, Ee-Kyung, Kim, Yoo-Jin, Lee, Eun Sun, Park, Seul Gi, Ji, Hye Min, Lee, Woo Hyung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873498/
https://www.ncbi.nlm.nih.gov/pubmed/35210507
http://dx.doi.org/10.1038/s41598-022-07139-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873498/
https://www.ncbi.nlm.nih.gov/pubmed/35210507
http://dx.doi.org/10.1038/s41598-022-07139-x

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