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
Multi-objective optimization determines when, which and how to fuse deep networks: an application to predict COVID-19 outcomes
Valerio Guarrasi, Paolo Soda
Implementing a Real-Time, YOLOv5 based Social Distancing Measuring System for Covid-19
Narayana Darapaneni, Shrawan Kumar, Selvarangan Krishnan, Hemalatha K, Arunkumar Rajagopal, Nagendra, Anwesh Reddy Paduri
Analysis of the use of color and its emotional relationship in visual creations based on experiences during the context of the COVID-19 pandemic
César González-Martín, Miguel Carrasco, Germán Oviedo
ST-FL: Style Transfer Preprocessing in Federated Learning for COVID-19 Segmentation
Antonios Georgiadis, Varun Babbar, Fran Silavong, Sean Moran, Rob Otter