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
Coronavirus disease situation analysis and prediction using machine learning: a study on Bangladeshi population
Al-Akhir Nayan, Boonserm Kijsirikul, Yuji Iwahori
Forecasting COVID-19 spreading trough an ensemble of classical and machine learning models: Spain's case study
Ignacio Heredia Cacha, Judith Sainz-Pardo Díaz, María Castrillo Melguizo, Álvaro López García
A Deep Ensemble Learning Approach to Lung CT Segmentation for COVID-19 Severity Assessment
Tal Ben-Haim, Ron Moshe Sofer, Gal Ben-Arie, Ilan Shelef, Tammy Riklin-Raviv
CNN-based Local Vision Transformer for COVID-19 Diagnosis
Hongyan Xu, Xiu Su, Dadong Wang
Cov3d: Detection of the presence and severity of COVID-19 from CT scans using 3D ResNets
Robert Turnbull