Artificial intelligence and innovation to optimize the tuberculosis diagnostic process

• Main Authors: Walter H. Curioso, Maria J. Brunette
• Format: Article
• Language: Spanish
• Published: Instituto Nacional de Salud 2020-09-01
• Series: Revista Peruana de Medicina Experimental y Salud Pública
• Subjects: tuberculosis; diagnóstico; inteligencia artificial; invenciones; salud urbana; perú
• Online Access: https://rpmesp.ins.gob.pe/index.php/rpmesp/article/view/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.