Team: NeuroVision
This initiative captures pixel distances between key anatomical points and processes this data to generate real-time bedside testing results. These results can be used to assess the difficulty of maintaining a patient’s airway.
![The AI-based Pre-Hospital Emergency Airway Assessment system (XAI-PEA) was developed by the X-Fea team. Photo courtesy of X-Fea](https://vcdn1-sohoa.vnecdn.net/2024/11/04/Cover-image-of-product-Dong-Hw-5703-7249-1730717385.jpg?w=680&h=0&q=100&dpr=1&fit=crop&s=hM1dC7RBPswg4iV5DK2fUA)
The AI-based Pre-Hospital Emergency Airway Assessment system (XAI-PEA) was developed by the X-Fea team. Photo courtesy of X-Fea
Subsequently, these findings are converted into clinical metrics and shared with healthcare providers through a connected system. Additionally, the system can send these results to multiple healthcare providers, enabling real-time collective assessments and ensuring that medical staff are well-prepared for patient intake and appropriate interventions.