Por favor, use este identificador para citar o enlazar este ítem: https://repositorio.cetys.mx/handle/60000/1768
Registro completo de metadatos
Campo DC Valor Lengua/Idioma
dc.contributor.authorHirales-Carbajal, Adan-
dc.contributor.authorEscobedo Bravo, Lizbeth Olivia-
dc.description.abstractWorldwide Fetal-Maternal morbidity and mortality is frightfully high. Most of these diseases occur in developing countries. One of the main reasons of this problem, after gestational hypertension and complications in childbirth, is infections. Infections are most of the times hard to detect by the patient. Urinary Tract Infections (UTI) during pregnancy is one of the main reasons of fetal-maternal morbidity and mortality in Mexico. Among others, the pervasiveness and heterogeneity of data generated complicates early diagnosis and treatment of UTI. In this study, two hundred, randomly chosen, medical records and notes corresponding to pregnant patients with and without UTI were analyzed to find association rules for UTI positive cases. We found that most of the occurring rules show how physicians strive toward discovering the presence of sexually transmitted diseases or infections and that patients are less likely to be auscultated for symptoms that lead to miscarriage. A four-phase data analysis workflow, referred to as UTIW (Urinary Tract Infection Workflow) for discovering association rules in patients with UTI is proposed.es_ES
dc.rightsAtribución-NoComercial-CompartirIgual 2.5 México*
dc.subjectApplied computinges_ES
dc.subjectLife and medical scienceses_ES
dc.subjectHealth care information systemses_ES
dc.titleUTIW: Urinary Tract Infection Workflow System towards early and automatic detection of Urinary Infection during pregnancyes_ES
dc.typeWorking Paperes_ES
dc.subject.sedeCampus Tijuanaes_ES
Aparece en las colecciones: Ponencias

Ficheros en este ítem:
No hay ficheros asociados a este ítem.

Este ítem está protegido por copyright original

Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons Creative Commons