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  "path": "/news/2026-06-hospital-ai-tool-blood-sugar.html",
  "publishedAt": "2026-06-27T10:00:03.000Z",
  "site": "https://medicalxpress.com",
  "textContent": "Cedars-Sinai Health Sciences University investigators developed an AI-based model that can identify hospitalized patients at risk of low blood sugar up to 24 hours before the condition occurs. The long short-term memory (LSTM) model, described in npj Digital Medicine, could help clinicians intervene earlier and prevent complications, including, in severe cases, seizures, coma and long-term heart arrhythmias.",
  "title": "Hospital AI tool predicts low blood sugar in patients up to 24 hours in advance"
}