ICHD3 Primary Headache Syndromes in Matrix and Graphical Representation

63 basis vectors span the space of all primary headache phenotypes in the ICHD3 classification, enabling automated diagnosis. The dataset encodes headache diagnoses as a matrix where rows are phenotypes and columns are characteristics, derived from the International Classification of Headache Disorders. Pengfei Zhang published this analysis on figshare in 2026.

Use Cases

• Automated headache diagnosis based on logical criteria encoded in a matrix.
• Systematic investigation of relationships between headache types and phenotypes using graph projections.
• Analysis of diagnostic fragmentation, such as identifying that paroxysmal hemicrania comprises 9 clusters.
• Dimensionality reduction of clinical criteria by representing diagnoses in a 63-dimensional vector space.

Strengths

• Derived from the ICHD3, the gold standard for headache clinical trials and research.
• Enables three concrete applications: large-scale systematic investigations, graphical representation, and improved diagnostic accuracy.
• Identifies 63 core characteristics, such as duration and aura features, that form the basis for all headache diagnoses.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect the specific interpretation bias inherent to the authors' matrix translation method.

Provenance

Source

figshare

Collection Method

Matrix translation of the International Classification of Headache Disorders (ICHD3) criteria.

Freshness

Last updated 2026-05-11 14:55:32; freshness should be verified.