Melissa McGonnell, Matt Orr, Joan Backman, Shannon A Johnson, Fiona Davidson, Penny Corkum
Examining the role of the visuospatial sketchpad in children's math calculation skills using Baddeley and Hitch's model of working memory
Acta psychologica
automatic disease diagnosis utilizing clinical data suffering issues feature sparse high probability missing values since graph neural network effective tool model structural information infer missing values becoming dominant method predictive model construction electronic medical records existing graph neural network based solutions usually adopt medical concepts eg symptoms feature representation clinical data without considering underlying semantic relations limited discriminative capability medical concept cannot provide sufficient indicative information disease article proposes knowledgeguided graph attention network disease prediction beside extracting attributevalue structure largesize medical concept mutual information multiple medical concepts mentioned electronic medical records taken account graph construction meanwhile defined diseases associations medical concepts medical knowledge graph incorporated graph provides potentials enhance indicative impacts medical concepts directly related target disease spatial attention based graph encoders employed aggregate information directly neighbor nodes generate node embeddings compact features used disease diagnosis approach general one utilized build predictive model using chinese emrs different diseases empirical experiments performance evaluation conducted realworld copd emr dataset comparison study results show proposed model outperforms baseline methods illustrates effectiveness proposed model