A Mobile Health Solution for Diseases Control Transmitted by Aedes Aegypti Mosquito using Predictive Classifiers

In healthcare, uncertainty moments are frequent, especially when they come from diseases with similar signals and symptoms. This work proposes a mobile health application based on predictive classifiers as inference mechanism capable to support health professionals in the identification of diseases transmitted by the Aedes Aegypti mosquito. The proposed system identifies the most probable disease in the case of dengue and chikungunya, given a set of symptoms presented by a patient. This work evaluates the experiments by crossvalidation using real data, and the results show that decision tree perform well for the proposed solution.

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