Autism Diagnostic Interview-Revised (ADI-R): Clinical Assessment Data

Autism Diagnostic Interview-Revised (ADI-R) data, a standardized diagnostic tool for autism spectrum disorders. The dataset is associated with the work of author Michael Rutter and is listed on the paperswithcode platform. Specific details on the number of records, variables, and collection timeframe are not provided in the available metadata.

Use Cases

• Train a classifier to predict autism spectrum disorder from structured interview responses (inferred from domain, verify after download)
• Analyze correlations between specific behavioral domains and diagnostic outcomes (inferred from domain, verify after download)
• Benchmark diagnostic algorithms against a standardized clinical assessment (inferred from domain, verify after download)

Strengths

• Published on the paperswithcode platform, which aggregates datasets for AI/ML research.
• Associated with a well-known author and diagnostic instrument in the field of autism research.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Michael Rutter