Matches in SemOpenAlex for { <https://semopenalex.org/work/W4220756449> ?p ?o ?g. }
Showing items 1 to 59 of
59
with 100 items per page.
- W4220756449 abstract "Abstract Background Perinatal mortality in Ethiopia is the highest in Africa, with 68 per 1000 pregnancies intrapartum deaths (death during the delivery). It is mainly associated with home delivery, which contributes for more than 75% of perinatal deaths. Financial constraints have a significant impact on timely access to maternal health (MH) care. Financial incentives, such as health insurance, can address the demand- and supply-side factors. This study, hence, aims to predict perinatal mortality based on maternal health status and health insurance service using homogeneous ensemble machine learning methods Methods The data was collected from Ethiopian demographic health survey from 2011 to 2019 G.C. The data were pre-processed to get quality data that are suitable for a homogenous ensemble machine-learning algorithm to develop a model that predicts perinatal mortality. Results For constructing the proposed model, three experiments were conducted using random forest, gradient boosting, and cat boost algorithms. The overall accuracy of random forest, gradient boosting, and cat boost with 17 features is 89.95%, 90.24%, and 82%, respectively. Conclusions We finally concluded that perinatal mortality over time in Ethiopia is decreasing. We found out that perinatal mortality in Ethiopia is associated with risk factors such as community-based health insurance, mother's educational level, residence, mother age, wealth status, distance to the health facility, preterm, smoke cigarette, anemia level, haemoglobin level, and marital status." @default.
- W4220756449 created "2022-04-03" @default.
- W4220756449 creator A5004555291 @default.
- W4220756449 creator A5013755879 @default.
- W4220756449 creator A5053666856 @default.
- W4220756449 date "2022-03-22" @default.
- W4220756449 modified "2023-09-28" @default.
- W4220756449 title "Predicting Perinatal Mortality Based on Maternal Health Status and Health Insurance Service using Homogeneous Ensemble Machine Learning Methods" @default.
- W4220756449 doi "https://doi.org/10.21203/rs.3.rs-1445740/v1" @default.
- W4220756449 hasPublicationYear "2022" @default.
- W4220756449 type Work @default.
- W4220756449 citedByCount "0" @default.
- W4220756449 crossrefType "posted-content" @default.
- W4220756449 hasAuthorship W4220756449A5004555291 @default.
- W4220756449 hasAuthorship W4220756449A5013755879 @default.
- W4220756449 hasAuthorship W4220756449A5053666856 @default.
- W4220756449 hasBestOaLocation W42207564491 @default.
- W4220756449 hasConcept C114614502 @default.
- W4220756449 hasConcept C119857082 @default.
- W4220756449 hasConcept C144024400 @default.
- W4220756449 hasConcept C149923435 @default.
- W4220756449 hasConcept C169258074 @default.
- W4220756449 hasConcept C2776269092 @default.
- W4220756449 hasConcept C2781354955 @default.
- W4220756449 hasConcept C2908647359 @default.
- W4220756449 hasConcept C33923547 @default.
- W4220756449 hasConcept C41008148 @default.
- W4220756449 hasConcept C66882249 @default.
- W4220756449 hasConcept C71924100 @default.
- W4220756449 hasConcept C99454951 @default.
- W4220756449 hasConceptScore W4220756449C114614502 @default.
- W4220756449 hasConceptScore W4220756449C119857082 @default.
- W4220756449 hasConceptScore W4220756449C144024400 @default.
- W4220756449 hasConceptScore W4220756449C149923435 @default.
- W4220756449 hasConceptScore W4220756449C169258074 @default.
- W4220756449 hasConceptScore W4220756449C2776269092 @default.
- W4220756449 hasConceptScore W4220756449C2781354955 @default.
- W4220756449 hasConceptScore W4220756449C2908647359 @default.
- W4220756449 hasConceptScore W4220756449C33923547 @default.
- W4220756449 hasConceptScore W4220756449C41008148 @default.
- W4220756449 hasConceptScore W4220756449C66882249 @default.
- W4220756449 hasConceptScore W4220756449C71924100 @default.
- W4220756449 hasConceptScore W4220756449C99454951 @default.
- W4220756449 hasLocation W42207564491 @default.
- W4220756449 hasOpenAccess W4220756449 @default.
- W4220756449 hasPrimaryLocation W42207564491 @default.
- W4220756449 hasRelatedWork W1954094490 @default.
- W4220756449 hasRelatedWork W2018819622 @default.
- W4220756449 hasRelatedWork W2021018230 @default.
- W4220756449 hasRelatedWork W2140259566 @default.
- W4220756449 hasRelatedWork W2247171671 @default.
- W4220756449 hasRelatedWork W2408714517 @default.
- W4220756449 hasRelatedWork W249507002 @default.
- W4220756449 hasRelatedWork W3216960987 @default.
- W4220756449 hasRelatedWork W4298370715 @default.
- W4220756449 hasRelatedWork W81005048 @default.
- W4220756449 isParatext "false" @default.
- W4220756449 isRetracted "false" @default.
- W4220756449 workType "article" @default.