A Homogeneous Ensemble of Robust Pre-defined Neural Network Enables Automated Annotation of Human Embryo Morphokinetics

BACKGROUND: The purpose of the current study was to reduce the risk of human bias in assessing embryos by automatically annotating embryonic development based on their morphological changes at specified time-points with convolutional neural network (CNN) and artificial intelligence (AI). METHODS: Ti...

Descripción completa

Detalles Bibliográficos
Autores principales: Danardono, Gunawan B., Erwin, Alva, Purnama, James, Handayani, Nining, Polim, Arie A., Boediono, Arief, Sini, Ivan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Avicenna Research Institute 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674456/
https://www.ncbi.nlm.nih.gov/pubmed/36452194
http://dx.doi.org/10.18502/jri.v23i4.10809

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674456/
https://www.ncbi.nlm.nih.gov/pubmed/36452194
http://dx.doi.org/10.18502/jri.v23i4.10809

Ejemplares similares