{"version":"1.0","type":"rich","title":"Gist 9633197","description":"This example demonstrates a simulated data analysis workflow for studying brain volume (BV) differences between healthy controls (HC) and multiple sclerosis (MS) patients across two sites. The notebook defines a synthetic data generator that creates age, disability (EDSS), and brain volume measurements for healthy controls and MS patients under two different scanning protocols, then calibrates measurements between the two sites. Using ordinary least squares regression via the `statsmodels` library, it fits models relating brain volume to age and disease severity, then applies a calibration transformation to harmonize measurements across sites. The visualization likely shows scatter plots of the simulated data with regression lines, illustrating the calibration process and residual patterns. The example demonstrates a statistical approach to cross-site calibration of imaging biomarkers in the presence of disease-related effects.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-9633197?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}