ruthlys commited on
Commit
e958c17
1 Parent(s): 5a1a9cf

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +10 -4
README.md CHANGED
@@ -9,12 +9,18 @@ pretty_name: rabies_diagnosis
9
 
10
  # Machine Learning Dataset for Rabies Diagnosis and Outbreak Prediction
11
 
12
- Contact:
13
 
14
- - Asa Emmanuel at asakalonga@gmail.com and Kennedy Lushasi at klushasi@ihi.or.tz
 
 
15
 
16
  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.
17
 
18
- Authors and Affiliations:
 
 
 
 
19
 
20
- - Asa Emmanuel, Rebecca Chaula, Deogratias Mzurikwao, Joel Changalucha, Kennedy Lushasi
 
9
 
10
  # Machine Learning Dataset for Rabies Diagnosis and Outbreak Prediction
11
 
12
+ ## Contact
13
 
14
+ Asa Emmanuel at asakalonga@gmail.com and Kennedy Lushasi at klushasi@ihi.or.tz
15
+
16
+ ## Dataset
17
 
18
  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.
19
 
20
+ ## Authors and Affiliations
21
+
22
+ Asa Emmanuel, Rebecca Chaula, Deogratias Mzurikwao, Joel Changalucha, Kennedy Lushasi
23
+
24
+ ## How to cite
25
 
26
+ You can cite all versions by using [DOI 10.5281/zenodo.10068425](https://zenodo.org/doi/10.5281/zenodo.10068425).