Pediatric ADHD Treatment Response Prediction Data from Multicenter Study

figshare admin karger published supplementary material for a machine learning study on June 3, 2026. The dataset contains demographic, clinical, behavioral, and laboratory data from 809 children aged 6–12 years with ADHD. It was used to develop models predicting treatment response and adverse events for acupuncture combined with conventional care.

Use Cases

• Predict treatment response based on demographic, clinical, behavioral, and laboratory features mentioned in the description
• Predict adverse events based on parent-reported outcomes mentioned in the description
• Evaluate machine learning model performance for clinical decision support in integrative therapy settings
• Analyze feature importance for treatment outcomes using SHAP interpretability methods referenced in the description

Strengths

• Contains data from 809 pediatric patients, providing a substantial sample size
• Includes multiple data domains: demographic, clinical, behavioral, and laboratory
• Model performance was validated in an internal cohort and two external cohorts

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Data may reflect temporal and geographic bias inherent to the multicenter retrospective study design

Provenance

Source

figshare admin karger

Collection Method

Multicentre retrospective study using routinely collected clinical data

Freshness

Last updated 2026-06-03 05:55:23