Lacuna Fund health datasets reduce health disparities by helping providers and patients make decisions that lead to more equitable healthcare outcomes. These datasets can be used to train chatbots, provide reliable medical information to the public, assist with disease screening and diagnosis, and assess the health and treatment of large populations over time (e.g. maternal health or HIV data). Learn more and download released datasets below.
- Released datasets
- 6
- Contributing authors
- 5+
- Access & licensing
- Open
- Domain area
- Health
Why it matters
Health and machine learning
Locally owned by design
Every dataset here was produced by teams in low- and middle-income contexts and is openly accessible to the international community.
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Machine Learning Dataset for Rabies Diagnosis and Outbreak Prediction
This dataset will help in the real-time and remote diagnosis of rabies disease for humans and animals in low-resource settings. A time series approach can be applied to the outbreak dataset to predict the number of rabies cases likely to occur within an area after a given time interval. This approach can help with resource mobilization, too, such as identifying the number of vaccines required in a specific area at a given time. The number of observations from the two datasets is 12,684. There are three datasets for rabies diagnosis for animals and humans, with 7,081 and 4,585 observations, respectively. In the outbreak prediction dataset, 1,018 observations were accounted for.
Released datasets
6 datasets
Search the collection, then expand an entry to see authors, descriptions and access links.
Showing 6 of 6