SGC-RML creates an 8D symptom atlas from multimodal PD data and integrates conformal calibration to deliver reliable, rejectable longitudinal assessments.
The Emerging Evidence of the Parkinson Pandemic
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
7T qMRI with DL segmentation and feature-selected ML reached 82% accuracy for PD vs HC, 100% for PIGD vs TD, and 73% multiclass on 45 subjects.
citing papers explorer
-
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.
-
7 Tesla Quantitative MRI and Machine Learning for Exploratory Motor Subtype Stratification and Diagnosis in Parkinson's Disease
7T qMRI with DL segmentation and feature-selected ML reached 82% accuracy for PD vs HC, 100% for PIGD vs TD, and 73% multiclass on 45 subjects.