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Prediction of adverse pregnancy outcomes using machine learning techniques: evidence from analysis of electronic medical records data in Rwanda

Published Online: 2025-02-12

Authors

Sylvain, Muzungu Hirwa

Nyabyenda, Emmanuel Christian

Uwase, Melissa

Komezusenge, Isaac

Ndikumana, Fauste

Ngaruye, Innocent
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Text and Data Mining valid from 2025-02-12

Version of Record valid from 2025-02-12
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Article History

Received: 12 October 2024

Accepted: 5 February 2025

First Online: 12 February 2025

Declarations

:

: Ethical approval for this study was obtained from the Institutional Review Board (IRB) of the University of Rwanda with reference number CMHS/IRB/338/2024. All data used in this research were anonymized before analysis to ensure the privacy and confidentiality of participants. Identifiable information such as patient names, national identification numbers, and addresses were removed in compliance with ethical standards. As this study involved secondary data analysis of retrospective electronic medical records, formal consent from participants was waived by the IRB, given that no direct interaction with patients occurred. This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki and relevant national guidelines.

: Not applicable.

: The authors declare no competing interests.

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