Emergency Department

Emergency department (ED) research focuses on improving patient flow, diagnostic accuracy, and resource allocation to address overcrowding and enhance patient outcomes. Current studies utilize machine learning, particularly deep learning models like convolutional neural networks (CNNs), Long Short-Term Memory networks (LSTMs), and transformer-based architectures (e.g., Temporal Fusion Transformer, Perceiver), often incorporating multimodal data (vital signs, ECGs, lab results, imaging, and even speech) for tasks such as diagnosis prediction, patient deterioration prediction, and length-of-stay estimation. These advancements aim to create more efficient and effective ED operations, leading to improved patient care and reduced healthcare system strain.