Hospital AI tool predicts low blood sugar in patients up to 24 hours in advance. 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.
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Trechos de apoio da pauta: 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.
- Ponto de atenção: hospital.
- Ponto de atenção: tool.
- Ponto de atenção: predicts.
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