19 Dataset

Research on COVID-19 datasets focuses on developing and validating AI models for various tasks, including disease detection from medical images (chest X-rays and CT scans) and audio signals (coughs, breathing), as well as analyzing social media data to identify misinformation and vaccine hesitancy. Common approaches utilize convolutional neural networks (CNNs), recurrent neural networks (RNNs like Bi-LSTM and Bi-GRU), and graph-based clustering algorithms, often employing ensemble methods to improve performance. These datasets and the resulting models are crucial for improving diagnostic accuracy, understanding public health responses to the pandemic, and informing future pandemic preparedness strategies.