ICHD3 Headache Syndromes Represented as a Matrix for Automated Diagnosis

63 basis vectors span the mathematical space of all primary headache phenotypes according to the International Classification of Headache Disorders. This 42.4 KB dataset encodes the ICHD3 classification as a biadjacency matrix, enabling automated diagnosis and analysis. The work by Pengfei Zhang, last updated in 2026, translates clinical criteria into a logical structure for computational exploration.

Use Cases

• Automated headache diagnosis based on logical criteria encoding.
• Systematic investigation of relationships between headache phenotypes and characteristics.
• Graphical representation and clustering of headache syndromes for clinical insight.
• Analysis of diagnostic fragmentation, such as the 9 clusters identified for paroxysmal hemicrania.

Strengths

• Derived from the ICHD3 gold standard for headache classification.
• Enables mathematical operations like row reduction, yielding 63 basis vectors.
• Markov clustering yields 64 clusters, demonstrating internal structure.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset's scope is limited to primary headaches from the ICHD3 classification.

Provenance

Source

figshare

Collection Method

Translation of ICHD3 diagnostic criteria into true/false statements to form a phenotype-characteristic matrix.

Freshness

Last updated 2026-05-11 14:55:34; freshness should be verified.