SGC-RML creates an 8D symptom atlas from multimodal PD data and integrates conformal calibration to deliver reliable, rejectable longitudinal assessments.
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Deep learning model on large uniform healthy MRI dataset achieves brain age MAE of 4.06 years (hold-out) and 4.21 years (independent set), with frontal lobe prominence and age gaps linked to neuropsychological scores.
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SGC-RML: A reliable and interpretable longitudinal assessment for PD in real-world DNS
SGC-RML creates an 8D symptom atlas from multimodal PD data and integrates conformal calibration to deliver reliable, rejectable longitudinal assessments.
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Estimating brain age based on a healthy population with deep learning and structural MRI
Deep learning model on large uniform healthy MRI dataset achieves brain age MAE of 4.06 years (hold-out) and 4.21 years (independent set), with frontal lobe prominence and age gaps linked to neuropsychological scores.