Fig 1.
Study selection.
Fig 2.
Models used in the works divided by the main problems.
Table 1.
Overview of the primary studies.
∓: The study seems to present a model overfitting or an inappropriate benchmarking methodology.
Table 2.
Characteristics of the data sets used to evaluate Machine Learning and Deep Learning models for arboviral diseases classification.
Table 3.
Distribution of samples per classes.
Fig 3.
Attributes found in the data sets.
Table 4.
Summary of all demographic, epidemiological and clinical data presented in data set used by the primary studies.
Table 5.
Summary of all non-clinical data (laboratory and others) presented in the data set used by the primary studies.
Fig 4.
Metrics used to evaluate the models proposed in the literature.