Endotracheal Tube Position Anomaly Alerting System (ETPAAS) leverages AI to automatically analyze chest X-ray images and determine whether an endotracheal tube is properly positioned. It provides timely alerts for healthcare professionals to verify and correct malposition, thereby reducing complications and tube dislodgement, enhancing the quality of care, and ensuring patient safety. The model delivers strong performance, achieving accuracy of about 95% in object detection and about 90% accuracy in evaluating tube position appropriateness.

This technology integrates the YOLO algorithm model with chest X-ray imaging to automatically detect endotracheal tube (ETT) position and provide alerts. It overcomes the limitations of traditional manual interpretation and external markings, offering real-time, objective, and highly accurate decision support. With cross-hospital validation showing accuracy of over 90%, the system demonstrates strong potential for clinical application, commercialization, and expansion to other medical utilities.

This technology automatically detects ETT position and sends real-time alerts. Cross-hospital validation confirmed clinical benefits. It targets global markets including Taiwan, U.S.A., Asia-Pacific, and Europe, with promising financial outlook. The business model focuses on licensing and co-development with medical software and ICU integrators, leveraging existing platforms for rapid growth and stable profits, offering strong commercialization prospects.