Graph convolutional network with attention mechanism improve major depressive depression diagnosis based on plasma biomarkers and neuroimaging data.

Background: The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presentations. Despite extensive machine learning studies in psychiatric diagnosis, a reliable tool integrating multi-modality data is still lacking.

[Spatial Prediction Modeling for Soil pH Based on Multiscale Geographical Weighted Regression(MGWR) and Its Influencing Factors].

Anhui, Henan, Jiangsu, and Shandong provinces were selected as the study area. A total of 599 soil samples and nine environmental factors of soil pH were collected. The spatial distribution of soil pH was modeled based on multi-scale geographically weighted regression(MGWR), mixed geographically weighted regression(Mixed GWR), geographically weighted regression(GWR), and multiple linear regression(MLR) models.