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Published April 30, 2025 | Version 1
Dataset Open

Dataset for Maternal Health Risks Stratification (MHRS) in Tanzania

Authors/Creators

  • 1. ROR icon The University of Dodoma
  • 2. The University of Dodoma College of Informatics and Virtual Education
  • 3. ROR icon Muhimbili National Hospital

Contributors

Hosting institution:

Sponsor:

Description

The dataset is a collection of clinical parameters of pregnant women from Chamwino District in Dodoma region within the Central Zone, Mkuranga District in Pwani region within the Coastal Zone, Meatu District in  Simiyu region within Lake Zone, Mbulu District in Manyara region within the Northern Zone and Kilolo District in Iringa region within Southern Highlands. To ensure diversity and the inclusion of underserved communities in the dataset, the study collected and stratified data from 8,817 pregnant women attending maternity primary health facilities for over nine months.

This dataset was developed to support machine learning applications that stratify maternal health risks in underserved communities across Tanzania. It enables research and development of predictive models to identify high-risk pregnancies, inform timely interventions, and improve maternal and newborn health outcomes. The dataset can also be used for public health research, benchmarking maternal health indicators, and building educational tools for community and clinical settings.

Files

maternal_dataset_csv.csv

Files (15.2 MB)

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md5:0253d2d385dd80d6c9bb82df6b85fcc8
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Additional details

Related works

Describes
Dataset: 10.17632/p5w98dvbbk.1 (DOI)

Funding

Wellcome Trust
Lacuna Fund: Machine Learning Datasets for More Equitable Health Outcomes 228079

Dates

Collected
2024-05-20
Started data collection
Collected
2025-03-30
Ended data collection
Created
2025-04-30
Dataset Created

References

  • 1. Mojumdar, Mayen Uddin ; Assaduzzaman, Md; Sarker, Dhiman; Shifa, Hasin Arman; Sajeeb, Md. Anisul Haque; Bari , Shadikul; Chakraborty, Narayan Ranjan; Alam, Mohammad Jahangir (2024), "Maternal Health Risk Assessment Dataset", Mendeley Data, V1, doi: 10.17632/p5w98dvbbk.1
  • 2. Ahmed, M. (2020). Maternal Health Risk [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5DP5D.
  • 3. Ahmed M., Kashem M.A., Rahman M., Khatun S. (2020) Review and Analysis of Risk Factor of Maternal Health in Remote Area Using the Internet of Things (IoT). In: Kasruddin Nasir A. et al. (eds) InECCE2019. Lecture Notes in Electrical Engineering, vol 632. Springer, Singapore.