[Revista Médica del IMSS: Institutional heritage and Important reference]

<p><strong>Abstract</strong></p><p>In a context that has tended towards globalization, in which obtaining economic resources is usually the driving force of societies, information resources have frequently been treated as private goods for which one must pay. A strategy for the above has been open and free access to information, a factor of great importance for the construction of more open media. </p><p>En un contexto que ha tendido a lo globalizado, en el que la obtención de recursos económicos suele ser el motor de las sociedades, los recursos de información han sido tratados con frecuencia como bienes privados por los que hay que pagar. Una estrategia a lo anterior ha sido el acceso abierto y gratuito a la información, un factor de gran importancia para la construcción de medios más abiertos.</p><p>In a context that has tended towards globalization, in which obtaining economic resources is usually the driving force of societies, information resources have frequently been treated as private goods for which one must pay. A strategy for the above has been open and free access to information, a factor of great importance for the construction of more open media. </p&gt

Effectiveness of a diagnostic algorithm for dengue based on an artificial neural network

Introduction Dengue is a disease with a wide clinical spectrum. The early identification of dengue cases is crucial but challenging for health professionals; therefore, it is necessary to have effective diagnostic instruments to initiate timely care. Objective To evaluate the effectiveness of an algorithm based on an artificial neural network (ANN) to diagnose dengue in an endemic area. Methods A single-center case–control study was conducted in a secondary-care hospital in Ciudad Obregón, Sonora. An algorithm was built with the official operational definitions, which was called the “direct algorithm,” and for the ANN algorithm, the brain.js library was used. The data analysis was performed with the diagnostic tests of sensitivity, specificity, positive predictive value (ppv), and negative predictive value (npv), with 95% confidence intervals and Cohen's kappa index. Results A total of 233 cases and 233 controls from 2022 were included. The ANN presented a sensitivity of 0.90 (95% CI [0.85, 0.94]), specificity of 0.82 (95% CI [0.77, 0.87]), npv of 0.91 (95% CI [0.87, 0.94]) and ppv of 0.81 (95% CI [0.76, 0.85]) and a kappa of 0.72. The direct algorithm had a sensitivity of 0.97 (95% CI [0.94, 0.99]), specificity of 0.96 (95% CI [0.92, 0.98]), npv 0.97 (95% CI [0.94, 0.98]), ppv 0.96 (95% CI [0.93, 0.98]) and kappa 0.93. Conclusions The direct algorithm performed better than the ANN in the diagnosis of dengue