A Public Health Approach to Automated Pain Intensity Recognition in Chest Pain Patients via Facial Expression Analysis for Emergency Care Prioritization
Facial expression analysis improves diagnostic accuracy in chest pain patients, indicating potential for real-time monitoring using smartphones and laptops.
Key Points
Automating pain recognition enhances diagnostic accuracy by analyzing facial expressions in patients with chest pain, which is crucial for emergency care.
The system demonstrates 97% precision using a custom YOLOv4 model, ensuring it is effective for real-time assessment.
Utilizing smartphones and laptops allows healthcare providers to monitor pain levels flexibly and efficiently in various settings.
The approach is significant for supporting clinical observation without inferring myocardial infarction causes, highlighting its potential use in diverse healthcare environments.