Researchers have developed a new meta-taxonomy called NOMAD to systematically classify disease names based on their origins and naming conventions. This taxonomy, comprising 9 top-level categories and 20 subcategories, was applied to over 22,000 index entries from the ICD-10-CM 2026 Alphabetical Index using a machine learning pipeline. The study found that anatomical categories were the most prevalent naming convention, followed by descriptive and pathophysiological labels, while eponymous and geographical names were less common than their cultural prominence might suggest. AI
排序理由 The cluster contains an academic paper detailing a new classification system for medical nomenclature. [lever_c_demoted from research: ic=1 ai=0.4]
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