{ "story_id": "a6f5df367e6ac4080cce5561b328eb44", "desk": "drm3", "revision": 1, "published_at": "2026-09-02T08:01:45.000Z", "content_hash": "6036146caf7e6851364cc973ba80310a6126f44f28914395d9d66a29720df176", "hash_basis": "sha256 over `headline\\ndek\\nprose`, plus `\\n` + the canonical citations JSON when any source is placed, plus `\\n#blog` for blogs", "basis": { "headline": "AI analysis of 43,000 health records reveals migraine's systemic signature and four subgroups", "dek": "NTNU AI study of 43,000 health records finds migraine leaves bodywide traces and has four subgroups.", "prose": "Researchers at NTNU developed an AI model that used 60 non-headache variables such as age, sex, constipation, medication use, and back pain, and the model distinguished people with migraine from those without headaches. [^1]\n\nThe NTNU researchers' AI analysis identified four distinct subgroups of migraine: an all-male group, a group with prominent neck pain, a group with musculoskeletal pain, anxiety, and depression, and a group with classic migraine including aura. [^2]\n\nAnker Stubberud said the AI model's ability to identify migraine without headache data suggests the condition leaves biological traces that extend far beyond the attacks. [^3]\n\nAnker Stubberud, a physician and headache researcher at NTNU, said there are no blood tests or biological tests for migraine and that AI could help make correct diagnoses. [^4]\n\nHumans developed writing approximately 5,500 years ago, a skill that was key to the development of civilization and allowed us to record our history. [^5]\n\nThe study noted that the presence of oscillations in theta and alpha bands increases, which is linked to working memory, sustained attention, and the acquisition of new learning. 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