COVID 19 Diagnosis
COVID-19 diagnosis research focuses on developing rapid, accurate, and accessible methods to identify infections, supplementing or replacing the gold standard RT-PCR test. Current efforts utilize various data sources, including chest X-rays and CT scans, blood test parameters, and even respiratory audio recordings, analyzed with deep learning models like CNNs, Vision Transformers, and ensemble methods. These AI-driven approaches aim to improve diagnostic speed and efficiency, particularly in resource-constrained settings, and enhance the interpretability of diagnostic results for clinicians. The ultimate goal is to improve patient outcomes and public health management through more effective and readily available diagnostic tools.
Papers
Automatic COVID-19 disease diagnosis using 1D convolutional neural network and augmentation with human respiratory sound based on parameters: cough, breath, and voice
Kranthi Kumar Lella, Alphonse Pja
A literature review on COVID-19 disease diagnosis from respiratory sound data
Kranthi Kumar Lella, Alphonse PJA