The Application of Large Language Model in Emergency Chest Pain Triage

The Application of Large Language Model in Emergency Chest Pain Triage

This study will evaluate the accuracy and efficiency of large language model in emergency triage.

The study is to evaluate the value of large language model in emergency triage, their accuracy and efficiency were evaluated and compared with traditional triage. To explore whether the model can effectively reduce the workload of medical staff, while improving the speed and quality of triage. In addition, the ability of the model to predict serious medical events such as acute heart events and strokes was evaluated. It also included surveys of patients; acceptance and satisfaction with the use of the artificial intelligence-assisted triage system. Analyze the economic benefits of adopting this technology, including cost saving and optimal allocation of resources.

Inclusion Criteria:

1. All patients with chest pain entered the emergency triage procedure.
2. patients aged 18 and above.

Exclusion Criteria:

1. Patients with severe cognitive impairment or inability to communicate.
2. There are patients who have been explicitly referred to specific departments (for example, some of the 120 transfer patients, who may go directly to the green channel) .
3. Patients with unstable vital signs .
4. Patients with potential medical problems.
5. Is participating in other clinical trials.
6. Failure to follow test procedures.
7. Those who refuse to sign the informed consent form.