{"version":"1.0","type":"rich","title":"Gist e5affea97473980182b59a9d4efb945e","description":"This example visualizes the relationship between brain connectivity measures and disability in multiple sclerosis patients. It fits ordinary least squares regression models predicting the EDSS score from diffusion imaging metrics and demographic covariates across each brain connection, then displays the resulting p-values and R-squared values in a table. The code uses pandas for data handling, statsmodels' `ols` API for the regression models, and seaborn with pylab inline for plotting.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-e5affea97473980182b59a9d4efb945e?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}