Machine learning and deep learning techniques to support clinical diagnosis of arboviral diseases: A systematic review.

ABSTRACT:

Background

Neglected tropical diseases (NTDs) primarily affect the poorest populations, often living in remote, rural areas, urban slums or conflict zones. Arboviruses are a significant NTD category spread by mosquitoes. Dengue, Chikungunya, and Zika are three arboviruses that affect a large proportion of the population in Latin and South America. The clinical diagnosis of these arboviral diseases is a difficult task due to the concurrent circulation of several arboviruses which present similar symptoms, inaccurate serologic tests resulting from cross-reaction and co-infection with other arboviruses.

Objective

The goal of this paper is to present evidence on the state of the art of studies investigating the automatic classification of arboviral diseases to support clinical d

SUBMITTER: da Silva Neto SR 

PROVIDER: S-EPMC8791518 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature