NCT05115097Unknown不适用
AI Evaluation of COVID-19 Sounds
适应症
试验速览
- 阶段
- 不适用
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- Accuracy evaluation
研究概览
简要总结
In this study the investigators record sounds of voice, breaths and cough of subjects who tested positive for COVID19. The investigators then feed these sounds into an artificial intelligence and see if it can learn to recognise features to make COVID19 diagnosis from these sounds in order to avoid to use swabs to test the general population.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Adults who tested positive for SARS-CoV-2 currently admitted to hospital at the study site
- •Adults who tested negative for SARS-CoV-2 and are admitted for any respiratory condition (eg COPD or asthma flare-up, pneumonia..)
- •Healthy volunteers
排除标准
- •Patients under the age of
- •Patients unable to read in Italian.
- •Patients unable to give informed consent to participate.
- •Patients requiring life support (including, but not limited to, mechanical cardiac support, ventilation, etc.)
- •Patients who are pregnant
结局指标
主要结局
Accuracy evaluation
时间窗: September 2022-December 2022
The investigators will evaluate the accuracy of the ML algorithm in terms of sensitivity and specificity and ROC-AUC
次要结局
未报告次要终点
研究者
Emanuele Bosi
Clinical Professor, Head of Endocrino-Metabolic and Diabetologic Medicine
IRCCS San Raffaele
研究点 (1)
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