Core Insights - A new algorithm developed by a team from Shanghai's Tenth People's Hospital can accurately identify ST-segment elevation myocardial infarction (STEMI) patients through standard 12-lead electrocardiograms (ECGs), potentially reducing mortality rates and the risk of sudden cardiac death [1][3][4] - The success rate of treating acute myocardial infarction is highly time-dependent, with a significant difference in mortality rates between patients receiving rapid treatment and those experiencing delays [3] - The integration of artificial intelligence (AI) in analyzing ECG waveforms is expected to optimize emergency decision-making and improve patient outcomes [3][4] Technology Development - The research team has developed a wearable 12-lead ECG vest, which has received national Class II medical registration and is now in mass production [4] - The vest automatically transmits ECG signals to the cloud, where software can provide alerts for myocardial infarction and malignant arrhythmias [4] - The team has compiled over 10,000 preoperative ECG data samples and is expanding its dataset to enhance the AI's ability to identify and locate myocardial infarction [4] Future Implications - The AI-driven ECG system aims to provide efficient early warnings for high-risk groups and postoperative patients, potentially lowering the incidence of myocardial infarction and sudden cardiac death [4] - The system may also enhance the capabilities of emergency departments and chest pain centers in identifying acute myocardial infarction, thereby improving patient prognosis [4]