Abstract

CURIOSO, Walter H.  and  BRUNETTE, Maria J.. Artificial intelligence and innovation to optimize the tuberculosis diagnostic process. Rev. perú. med. exp. salud publica [online]. 2020, vol.37, n.3, pp.554-558. ISSN 1726-4634.  http://dx.doi.org/10.17843/rpmesp.2020.373.5585.

Tuberculosis remains an urgent issue on the urban health agenda, especially in low- and middle-income countries. There is a need to develop and implement innovative and effective solutions in the tuberculosis diagnostic process. In this article, We describe the importance of artificial intelligence as a strategy to address tuberculosis control, particularly by providing timely diagnosis. Besides technological factors, the role of socio-technical, cultural and organizational factors is emphasized. The eRx tool involving deep learning algorithms and specifically the use of convolutional neural networks is presented as a case study. eRx is a promising artificial intelligence-based tool for the diagnosis of tuberculosis; which comprises a variety of innovative techniques involving remote X-ray analysis for suspected tuberculosis cases. Innovations based on artificial intelligence tools can optimize the diagnostic process for tuberculosis and other communicable diseases.

Keywords : Tuberculosis; Diagnosis; Artificial Intelligence; Inventions; Urban Health; Peru.

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