Genetic algorithm–assisted machine learning for clinical pregnancy prediction in in vitro fertilization

BACKGROUND: A clinical pregnancy prediction model was developed by implementing machine learning technology that uses a combination of static images and medical data to calculate the outcome of an in vitro fertilization cycle. OBJECTIVE: To provide a system that can accurately and sufficiently assis...

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Detalles Bibliográficos
Autores principales: Louis, Claudio Michael, Handayani, Nining, Aprilliana, Tri, Polim, Arie A., Boediono, Arief, Sini, Ivan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758485/
https://www.ncbi.nlm.nih.gov/pubmed/36536794
http://dx.doi.org/10.1016/j.xagr.2022.100133

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758485/
https://www.ncbi.nlm.nih.gov/pubmed/36536794
http://dx.doi.org/10.1016/j.xagr.2022.100133

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