Assessing the risk of dengue severity using demographic information and laboratory test results with machine learning.
Sheng-Wen HuangHuey-Pin TsaiSu-Jhen HungWen-Chien KoJen-Ren WangPublished in: PLoS neglected tropical diseases (2020)
We developed prognostic models for the prediction of dengue severity in patients, using machine learning. The discriminative ability of the artificial neural network exhibited good performance for severe dengue prognosis. This model could help clinicians obtain a rapid prognosis during dengue outbreaks. However, the model requires further validation using external cohorts in future studies.
Keyphrases
- zika virus
- dengue virus
- aedes aegypti
- neural network
- machine learning
- end stage renal disease
- ejection fraction
- chronic kidney disease
- prognostic factors
- peritoneal dialysis
- patient reported outcomes
- artificial intelligence
- current status
- social media
- drug induced
- big data
- patient reported
- infectious diseases
- sensitive detection