Hospital AI tool predicts low blood sugar in patients up to 24 hours in advance

Article excerpt

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.