Supplementary material 1. S1 Comparison of the predictions obtained by the best performing statistical and machine learning techniques for different time horizons. S2 Boxplots of the absolute errors (

DataCite Commons2025-04-11 更新90

Replication Data for: Predicting Dengue Incidence Leveraging Internet-Based Data Sources. A Case Study in 20 cities in Brazil.

登革热预测

数字流行病学

Attached are the attendant data sources to the paper "Predicting Dengue Incidence Leveraging Internet-Based Data Sources. A Case Study in 20 cities in Brazil."

NIAID Data Ecosystem60

Additional file 2 of Biochemical and ultrasound predictors of ICU admission among hospitalized dengue patients in Bangladesh

登革热预测

临床数据辅助决策

Supplementary Material 2.

DataCite Commons2025-12-04 更新90

Projecting the future of dengue under climate change scenarios: Progress, uncertainties and research needs

气候变化与疾病传播

登革热预测

Background Dengue is a mosquito-borne viral disease and its transmission is closely linked to climate. We aimed to review available information on the projection of dengue in the future under climate

NIAID Data Ecosystem80

Regression results from the validation of the WADI-Dengue.

资源简介：

相关数据集