Performance of machine-learning approach for prediction of pre-eclampsia in a middle-income country.

Autor: Torres-Torres J; Clinical Research Branch, Instituto Nacional de Perinatología Isidro Espinosa de los Reyes, Mexico City, Mexico.; Obstetrics and Gynecology Department, The American British Cowdray Medical Center, Mexico City, Mexico., Villafan-Bernal JR; Laboratory of Immunogenomics and Metabolic Diseases, INMEGEN, Mexico City, Mexico., Martinez-Portilla RJ; Clinical Research Branch, Instituto Nacional de Perinatología Isidro Espinosa de los Reyes, Mexico City, Mexico., Hidalgo-Carrera JA; Obstetrics and Gynecology Department, The American British Cowdray Medical Center, Mexico City, Mexico., Estrada-Gutierrez G; Clinical Research Branch, Instituto Nacional de Perinatología Isidro Espinosa de los Reyes, Mexico City, Mexico., Adalid-Martinez-Cisneros R; Servicios de Salud Pública de la Ciudad de México, Mexico City, Mexico., Rojas-Zepeda L; Maternal-Fetal Medicine Department, Instituto Materno Infantil del Estado de México, Toluca, Mexico., Acevedo-Gallegos S; Clinical Research Branch, Instituto Nacional de Perinatología Isidro Espinosa de los Reyes, Mexico City, Mexico., Camarena-Cabrera DM; Clinical Research Branch, Instituto Nacional de Perinatología Isidro Espinosa de los Reyes, Mexico City, Mexico., Cruz-Martínez MY; Centro de Investigación en Ciencias de la Salud, Universidad Anáhuac México Campus Norte, Huixquilucan, Mexico., Espino-Y-Sosa S; Clinical Research Branch, Instituto Nacional de Perinatología Isidro Espinosa de los Reyes, Mexico City, Mexico.; Obstetrics and Gynecology Department, The American British Cowdray Medical Center, Mexico City, Mexico.; Centro de Investigación en Ciencias de la Salud, Universidad Anáhuac México Campus Norte, Huixquilucan, Mexico.

Publikováno v: Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology [Ultrasound Obstet Gynecol] 2024 Mar; Vol. 63 (3), pp. 350-357.