Coswara: A website application enabling COVID-19 screening by analysing respiratory sound samples and health symptoms
원문 초록
The COVID-19 pandemic has accelerated research on design of alternative, quick and effective COVID-19 diagnosis approaches. In this paper, we describe the Coswara tool, a website application designed to enable COVID-19 detection by analysing respiratory sound samples and health symptoms. A user using this service can log into a website using any device connected to the internet, provide there current health symptom information and record few sound sampled corresponding to breathing, cough, and speech. Within a minute of analysis of this information on a cloud server the website tool will output a COVID-19 probability score to the user. As the COVID-19 pandemic continues to demand massive and scalable population level testing, we hypothesize that the proposed tool provides a potential solution towards this.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Region-specific Risk Quantification for Interpretable Prognosis of COVID-19
COVID-19 detection from pulmonary CT scans using a novel EfficientNet with attention mechanism
Improving Fairness of Automated Chest X-ray Diagnosis by Contrastive Learning
CT-xCOV: a CT-scan based Explainable Framework for COVid-19 diagnosis
C2C: Cough to COVID-19 Detection in BHI 2023 Data Challenge
COVID-19 detection using ViT transformer-based approach from Computed Tomography Images
토론
이 논문과 연결된 포럼 글이 아직 없습니다.