Prediction of caesarean section birth using machine learning algorithms among pregnant women in a district hospital in Ghana.
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| Title: | Prediction of caesarean section birth using machine learning algorithms among pregnant women in a district hospital in Ghana. |
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| Authors: | Owusu FO; Juaben Government Hospital, Juaben, Ghana., Addai-Manu H; Juaben Government Hospital, Juaben, Ghana.; Onwe Government Hospital, Onwe, Ghana., Agbedinu ES; Juaben Government Hospital, Juaben, Ghana., Konadu E; Department of Epidemiology and Biostatistics, School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.; University Hospital, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana., Asenso L; Juaben Government Hospital, Juaben, Ghana., Addae M; Department of Epidemiology and Biostatistics, School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.; University Hospital, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana., Osarfo J; Department of Community Health, School of Medicine, University of Health and Allied Health Sciences, Ho, Ghana., Ampah BA; University Hospital, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana., Opoku DA; Department of Epidemiology and Biostatistics, School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. douglasopokuaninng@gmail.com.; University Hospital, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. douglasopokuaninng@gmail.com. |
| Source: | BMC pregnancy and childbirth [BMC Pregnancy Childbirth] 2025 Jul 02; Vol. 25 (1), pp. 690. Date of Electronic Publication: 2025 Jul 02. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 100967799 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2393 (Electronic) Linking ISSN: 14712393 NLM ISO Abbreviation: BMC Pregnancy Childbirth Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1471-2393 |
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| DOI: | 10.1186/s12884-025-07716-8 |
