Ventilator Associated Pneumonia
Ventilator-associated pneumonia (VAP) is a serious lung infection affecting patients requiring mechanical ventilation, posing significant mortality and healthcare resource burdens. Current research heavily emphasizes the development and application of machine learning models, particularly convolutional neural networks (CNNs) and other deep learning architectures like Vision Transformers, to improve early detection and risk prediction of VAP and other pneumonias, often using chest X-ray or CT scan images as input. These advancements aim to enhance diagnostic accuracy, potentially leading to earlier interventions and improved patient outcomes, particularly in resource-limited settings where expert radiologists may be scarce. The use of explainable AI (XAI) techniques is also gaining traction to increase the transparency and trustworthiness of these diagnostic tools.