Related papers: The smarty4covid dataset and knowledge base: a fra…

In this study, we proposed a machine learning-based system to distinguish patients with COVID-19 from non-COVID-19 patients by analyzing only a single cough sound. Two different data sets were used, one accessible for the public and the…

Due to the large accumulation of patients requiring hospitalization, the COVID-19 pandemic disease caused a high overload of health systems, even in developed countries. Deep learning techniques based on medical imaging data can help in the…

The COVID-19 pandemic demands assimilation of all available biomedical knowledge to decode its mechanisms of pathogenicity and transmission. Despite the recent renaissance in unsupervised neural networks for decoding unstructured natural…

One of the defining moments of the year 2020 is the outbreak of Coronavirus Disease (Covid-19), a deadly virus affecting the body's respiratory system to the point of needing a breathing aid via ventilators. As of June 21, 2020 there are…

SARS-CoV-2 is colloquially known as COVID-19 that had an initial outbreak in December 2019. The deadly virus has spread across the world, taking part in the global pandemic disease since March 2020. In addition, a recent variant of…

Ultrasound is fast becoming an inevitable diagnostic tool for regular and continuous monitoring of the lung with the recent outbreak of COVID-19. In this work, a novel approach is presented to extract acoustic propagation-based features to…

Ultrasound (US) is a non-invasive yet effective medical diagnostic imaging technique for the COVID-19 global pandemic. However, due to complex feature behaviors and expensive annotations of US images, it is difficult to apply Artificial…

Background and Objective: Artificial intelligence (AI) methods coupled with biomedical analysis has a critical role during pandemics as it helps to release the overwhelming pressure from healthcare systems and physicians. As the ongoing…

The aim of this paper was the detection of pathologies through respiratory sounds. The ICBHI (International Conference on Biomedical and Health Informatics) Benchmark was used. This dataset is composed of 920 sounds of which 810 are of…

The COVID19 pandemic, a unique and devastating respiratory disease outbreak, has affected global populations as the disease spreads rapidly. Recent Deep Learning breakthroughs may improve COVID19 prediction and forecasting as a tool of…

Audio-based classification techniques on body sounds have long been studied to aid in the diagnosis of respiratory diseases. While most research is centered on the use of cough as the main biomarker, other body sounds also have the…

While large language models have demonstrated impressive reasoning abilities, their extension to the audio modality, particularly within large audio-language models (LALMs), remains underexplored. Addressing this gap requires a systematic…

Since the emergence of COVID-19, deep learning models have been developed to identify COVID-19 from chest X-rays. With little to no direct access to hospital data, the AI community relies heavily on public data comprising numerous data…

The changing nature of the COVID-19 pandemic has highlighted the importance of comprehensively considering its impacts and considering changes over time. Most COVID-19 related research addresses narrowly focused research questions and is…

Phonation, or the vibration of the vocal folds, is the primary source of vocalization in the production of voiced sounds by humans. It is a complex bio-mechanical process that is highly sensitive to changes in the speaker's respiratory…

The COVID-19 epidemic is considered as the global health crisis of the whole society and the greatest challenge mankind faced since World War Two. Unfortunately, the fake news about COVID-19 is spreading as fast as the virus itself. The…

Monitoring public sentiment via social media is potentially helpful during health crises such as the COVID-19 pandemic. However, traditional frequency-based, data-driven neural network-based approaches can miss newly relevant content due to…

The COVID-19 pandemic underscored the importance of reliable, noninvasive diagnostic tools for robust public health interventions. In this work, we fused magnetic respiratory sensing technology (MRST) with machine learning (ML) to create a…

The disease called the new coronavirus (COVID19) is a new viral respiratory disease that first appeared on January 13, 2020 in Wuhan, China. Some of the symptoms of this disease are fever, cough, shortness of breath and difficulty in…

Auscultation of respiratory sounds is the primary tool for screening and diagnosing lung diseases. Automated analysis, coupled with digital stethoscopes, can play a crucial role in enabling tele-screening of fatal lung diseases. Deep neural…