Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387164116> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W4387164116 abstract "Abstract Objective Preeclampsia (PE) is a serious complication of pregnancy associated with maternal and fetal morbidity and mortality. Early‐onset and preterm preeclampsia have long‐term health implications for both mothers and infants. Current prediction models have limitations and may not be applicable in resource‐limited settings. Machine learning (ML) algorithms offer a potential solution for developing accurate and efficient prediction models. Methods We conducted a prospective cohort study in Mexico City to develop a first‐trimester prediction model for preterm preeclampsia (pPE) using ML. Maternal characteristics and locally developed multiples of the median (MoMs) for mean arterial pressure (MAP), uterine artery pulsatility index (UtA‐PI), and serum placental growth factor (PlGF) were used for variable selection. The dataset was split into training, validation, and test sets. An elastic net method was employed for predictor selection, and model performance was evaluated using area under the curve (AUC) and detection rates (DR) at 10% false positive rates (FPR). Results The final analysis included 3,050 pregnant women, of whom 124 (4.07%) developed PE. The ML model showed good performance, with AUCs of 0.897, 0.963, and 0.778 for pPE, early‐onset preeclampsia (ePE), and any type of preeclampsia (all‐PE), respectively. The DRs at 10% FPR were 76.5%, 88.2%, and 50.1% for pPE, ePE, and all‐PE, respectively. The ML model outperformed previous prediction models and showed better performance than external validations of existing algorithms. Conclusions Our ML model demonstrated high accuracy in predicting pPE and ePE using first‐trimester maternal characteristics and locally developed MoMs. The model could provide an efficient and accessible tool for early prediction of preeclampsia, facilitating timely interventions and improved maternal and fetal outcomes. This article is protected by copyright. All rights reserved." @default.
- W4387164116 created "2023-09-30" @default.
- W4387164116 creator A5012388664 @default.
- W4387164116 creator A5034206051 @default.
- W4387164116 creator A5046481971 @default.
- W4387164116 creator A5047146532 @default.
- W4387164116 creator A5050741144 @default.
- W4387164116 creator A5050875532 @default.
- W4387164116 creator A5065105796 @default.
- W4387164116 creator A5074050106 @default.
- W4387164116 creator A5081395700 @default.
- W4387164116 creator A5090380504 @default.
- W4387164116 creator A5092965559 @default.
- W4387164116 date "2023-09-29" @default.
- W4387164116 modified "2023-10-14" @default.
- W4387164116 title "Performance of a machine learning approach for the prediction of pre‐eclampsia in a middle‐income country" @default.
- W4387164116 doi "https://doi.org/10.1002/uog.27510" @default.
- W4387164116 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37774112" @default.
- W4387164116 hasPublicationYear "2023" @default.
- W4387164116 type Work @default.
- W4387164116 citedByCount "0" @default.
- W4387164116 crossrefType "journal-article" @default.
- W4387164116 hasAuthorship W4387164116A5012388664 @default.
- W4387164116 hasAuthorship W4387164116A5034206051 @default.
- W4387164116 hasAuthorship W4387164116A5046481971 @default.
- W4387164116 hasAuthorship W4387164116A5047146532 @default.
- W4387164116 hasAuthorship W4387164116A5050741144 @default.
- W4387164116 hasAuthorship W4387164116A5050875532 @default.
- W4387164116 hasAuthorship W4387164116A5065105796 @default.
- W4387164116 hasAuthorship W4387164116A5074050106 @default.
- W4387164116 hasAuthorship W4387164116A5081395700 @default.
- W4387164116 hasAuthorship W4387164116A5090380504 @default.
- W4387164116 hasAuthorship W4387164116A5092965559 @default.
- W4387164116 hasBestOaLocation W43871641161 @default.
- W4387164116 hasConcept C126322002 @default.
- W4387164116 hasConcept C131872663 @default.
- W4387164116 hasConcept C172680121 @default.
- W4387164116 hasConcept C188816634 @default.
- W4387164116 hasConcept C2777218350 @default.
- W4387164116 hasConcept C2779234561 @default.
- W4387164116 hasConcept C2781207646 @default.
- W4387164116 hasConcept C2781276381 @default.
- W4387164116 hasConcept C3019714739 @default.
- W4387164116 hasConcept C46973012 @default.
- W4387164116 hasConcept C54355233 @default.
- W4387164116 hasConcept C71924100 @default.
- W4387164116 hasConcept C72563966 @default.
- W4387164116 hasConcept C86803240 @default.
- W4387164116 hasConceptScore W4387164116C126322002 @default.
- W4387164116 hasConceptScore W4387164116C131872663 @default.
- W4387164116 hasConceptScore W4387164116C172680121 @default.
- W4387164116 hasConceptScore W4387164116C188816634 @default.
- W4387164116 hasConceptScore W4387164116C2777218350 @default.
- W4387164116 hasConceptScore W4387164116C2779234561 @default.
- W4387164116 hasConceptScore W4387164116C2781207646 @default.
- W4387164116 hasConceptScore W4387164116C2781276381 @default.
- W4387164116 hasConceptScore W4387164116C3019714739 @default.
- W4387164116 hasConceptScore W4387164116C46973012 @default.
- W4387164116 hasConceptScore W4387164116C54355233 @default.
- W4387164116 hasConceptScore W4387164116C71924100 @default.
- W4387164116 hasConceptScore W4387164116C72563966 @default.
- W4387164116 hasConceptScore W4387164116C86803240 @default.
- W4387164116 hasLocation W43871641161 @default.
- W4387164116 hasLocation W43871641162 @default.
- W4387164116 hasOpenAccess W4387164116 @default.
- W4387164116 hasPrimaryLocation W43871641161 @default.
- W4387164116 hasRelatedWork W2037748478 @default.
- W4387164116 hasRelatedWork W2074508600 @default.
- W4387164116 hasRelatedWork W2093828693 @default.
- W4387164116 hasRelatedWork W2095584749 @default.
- W4387164116 hasRelatedWork W2606562919 @default.
- W4387164116 hasRelatedWork W2902115400 @default.
- W4387164116 hasRelatedWork W3012384304 @default.
- W4387164116 hasRelatedWork W3015469752 @default.
- W4387164116 hasRelatedWork W3210091886 @default.
- W4387164116 hasRelatedWork W4287456338 @default.
- W4387164116 isParatext "false" @default.
- W4387164116 isRetracted "false" @default.
- W4387164116 workType "article" @default.