Covid 19
COVID-19 research continues to explore the pandemic's multifaceted impact, focusing on accurate prediction of disease severity and mortality, effective diagnosis and treatment strategies, and understanding the spread of misinformation. Current research leverages machine learning, particularly deep learning models like convolutional neural networks and large language models, to analyze diverse data sources including chest X-rays, blood test parameters, and social media posts. These efforts aim to improve clinical decision-making, enhance public health interventions, and ultimately mitigate the long-term consequences of the pandemic.
Papers
Cross-dataset domain adaptation for the classification COVID-19 using chest computed tomography images
Ridha Ouni, Haikel Alhichri
Data and models for stance and premise detection in COVID-19 tweets: insights from the Social Media Mining for Health (SMM4H) 2022 shared task
Vera Davydova, Huabin Yang, Elena Tutubalina
COVID-19 Imposes Rethinking of Conferencing -- Environmental Impact Assessment of Artificial Intelligence Conferences
Pavlina Mitsou, Nikoleta-Victoria Tsakalidou, Eleni Vrochidou, George A. Papakostas
Text Augmentations with R-drop for Classification of Tweets Self Reporting Covid-19
Sumam Francis, Marie-Francine Moens