跳至主要内容
临床试验/jRCT1050210089
jRCT1050210089招募中不适用

COVID Triage Machine Learning Algorithm Using CT Images Multicenter Observational Study (AICOVID study)

Osaka General Medical Center0 个研究点目标入组 3,000 人开始时间: 2020年10月7日最近更新:

试验速览

阶段
不适用
状态
招募中
入组人数
3,000
主要终点
Predictive ability of a machine learning model

研究概览

简要总结

暂无简介。

研究设计

研究类型
Observational

入排标准

年龄范围
No limit 至 No limit(—)
性别
All

入选标准

  • Three groups of patients will be included in the study: patients with COVID and patients with pneumonia due to other infectious diseases who visited the Emergency Department or were admitted to the Emergency Department of the Osaka General Medical Center, and patients who had a chest CT scan as a screening (e.g., trauma patients with a normal chest CT image as a result). Patients at other participating centers will be selected according to the above criteria.

排除标准

  • (1) Patients who have refused to use the information after reading the information disclosure document
  • (2) Patients for whom the scope of imaging was inappropriate
  • (3) Patients with other data deficiencies
  • (4) Patients deemed inappropriate by the researcher.

结局指标

主要结局

Predictive ability of a machine learning model

Automatically analyzes laboratory images of COVID patients for COVID infection

Comparison with emergency department physicians

Ability to predict COVID infection

次要结局

未报告次要终点

研究者

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