Artificial intelligence and innovation to optimize the tuberculosis diagnostic process

Curioso W.H.; Brunette M.J. · Revista Peruana de Medicina Experimental y Salud Publica (2020) · DOI: 10.17843/rpmesp.2020.373.5585

Resumen

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. In-novations based on artificial intelligence tools can optimize the diagnostic process for tuberculosis and other communicable diseases.

Instituciones: Universidad Continental