Publications by authors named "Han-Song Wang"
Background: To promote the shared decision-making (SDM) between patients and doctors in pediatric outpatient departments, this study was designed to validate artificial intelligence (AI) -initiated medical tests for children with fever.
Methods: We designed an AI model, named Xiaoyi, to suggest necessary tests for a febrile child before visiting a pediatric outpatient clinic. We calculated the sensitivity, specificity, and F1 score to evaluate the efficacy of Xiaoyi's recommendations.
Artificial intelligence (AI) has been deeply applied in the medical field and has shown broad application prospects. Pre-consultation system is an important supplement to the traditional face-to-face consultation. The combination of the AI and the pre-consultation system can help to raise the efficiency of the clinical work.
View Article and Find Full Text PDFArticle Synopsis
- - The study assessed an AI algorithm's effectiveness in detecting breath sounds in children with pulmonary diseases, using data collected at the Shanghai Children's Medical Center from May to December 2019.
- - A total of 112 children contributed 672 breath sound recordings, with the AI showing a detection accuracy of 77.7%, significantly outperforming general pediatricians who had an accuracy of 59.9%.
- - Results indicated that the AI's performance varied by patient age, with the highest accuracy (81.3%) observed in children under 12 months, especially in identifying specific sounds like crackles and wheezes.