The Benefits of Artificial Intelligence Algorithms (CNNs) for Discriminating Between COVID-19 and Influenza Pneumonitis in an Emergency Department Using Chest X-Ray Examinations
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 200
- 试验地点
- 3
- 主要终点
- COVID-19 negative X-Rays
研究概览
简要总结
This project aims to use artificial intelligence (image discrimination) algorithms, specifically convolutional neural networks (CNNs) for scanning chest radiographs in the emergency department (triage) in patients with suspected respiratory symptoms (fever, cough, myalgia) of coronavirus infection COVID 19. The objective is to create and validate a software solution that discriminates on the basis of the chest x-ray between Covid-19 pneumonitis and influenza
详细描述
This project aims to use artificial intelligence (image discrimination) algorithms;
- specifically convolutional neural networks (CNNs) for scanning chest radiographs in the emergency department (triage) in patients with suspected respiratory symptoms (fever, cough, myalgia) of coronavirus infection COVID 19;
- the objective is to create and validate a software solution that discriminates on the basis of the chest x-ray between Covid-19 pneumonitis and influenza;
- this software will be trained by introducing X-Rays from patients with/without COVID-19 pneumonitis and/or flu pneumonitis;
- the same AI algorithm will run on future X-Ray scans for predicting possible COVID-19 pneumonitis
研究设计
- 研究类型
- Observational
- 观察模型
- Ecologic Or Community
- 时间视角
- Prospective
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •flu-like symptoms: myalgia, cough, fever, sputum
- •Chest X-Rays
- •COVID-19 biological tests
排除标准
- •patient refusal
- •uncertain radiographs
- •uncertain tests results
结局指标
主要结局
COVID-19 negative X-Rays
时间窗: 6 months
Number of participants with pneumonitis on Chest X-Ray and COVID 19 negative
COVID-19 positive X-Rays
时间窗: 6 months
Number of participants with pneumonitis on Chest X-Ray and COVID 19 positive
次要结局
未报告次要终点
研究者
Professor Adrian Covic
Clinical Professor
Grigore T. Popa University of Medicine and Pharmacy