通过对胸部计算机断层扫描图像应用人工智能来快速筛查 COVID-19:可行性研究。

Medicine access @ point of care Pub Date : 2021-05-16 eCollection Date: 2021-01-01 DOI:10.1177/23992026211013644
Pedro Galván, José Fusillo, Felipe González, Oraldo Vukujevic, Luciano Recalde, Ronald Rivas, José Ortellado, Juan Portillo, Julio Mazzoleni, Enrique Hilario
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摘要

目的:本研究旨在介绍巴拉圭公共卫生领域通过远程医疗应用人工智能(AI)快速诊断 COVID-19 的结果和影响:这是一项描述性、多中心、观察性设计的可行性研究,基于一种人工智能工具,用于在该国公立医院就诊的呼吸困难患者的胸部计算机断层扫描(CT)图像中快速检测 COVID-19。患者的数字 CT 图像被传输到人工智能诊断平台,几分钟后,放射科医生和 COVID-19 专业的肺科医生下载图像进行评估、确诊,并与基因诊断(反转录聚合酶链反应(RT-PCR))进行比较。此外,还确定了两个并行应用的类似人工智能系统之间的一致性百分比,以研究将其作为通过远程医疗筛查 COVID-19 患者的替代方法的可行性:结果:2020 年 3 月至 8 月间,全国 14 家医院对呼吸系统疾病患者进行了 911 次快速诊断检测,以排除 COVID-19 的可能性。患者平均年龄为 50.7 岁,62.6% 为男性,37.4% 为女性。大多数确诊的呼吸系统疾病发生在 27-59 岁年龄组(252 项研究),60 岁以上年龄组占第二位,19-26 岁年龄组占第三位。放射科医生/肺科医生最常发现的病症是重症肺炎、双侧肺炎伴胸腔积液、双侧肺气肿、弥漫性磨玻璃不透明、半膈肌麻痹、右下叶钙化肉芽肿、双侧胸腔积液、肺结核后遗症、双侧肺气肿和纤维化病变等。总体而言,两种人工智能系统的诊断结果平均一致率为 86%,不一致率为 14%。与 RT-PCR 相比,人工智能系统的灵敏度为 93%,特异性为 80%:巴拉圭拥有一套基于人工智能的远程医疗筛查系统,可从呼吸系统疾病患者的胸部 CT 图像中快速分层检测 COVID-19。这一应用加强了综合医疗服务网络,合理利用了专业人力资源、设备和实验室诊断投入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Rapid screening for COVID-19 by applying artificial intelligence to chest computed tomography images: A feasibility study.

Aim: The aim of the study was to present the results and impact of the application of artificial intelligence (AI) in the rapid diagnosis of COVID-19 by telemedicine in public health in Paraguay.

Methods: This is a descriptive, multi-centered, observational design feasibility study based on an AI tool for the rapid detection of COVID-19 in chest computed tomography (CT) images of patients with respiratory difficulties attending the country's public hospitals. The patients' digital CT images were transmitted to the AI diagnostic platform, and after a few minutes, radiologists and pneumologists specialized in COVID-19 downloaded the images for evaluation, confirmation of diagnosis, and comparison with the genetic diagnosis (reverse transcription polymerase chain reaction (RT-PCR)). It was also determined the percentage of agreement between two similar AI systems applied in parallel to study the viability of using it as an alternative method of screening patients with COVID-19 through telemedicine.

Results: Between March and August 2020, 911 rapid diagnostic tests were carried out on patients with respiratory disorders to rule out COVID-19 in 14 hospitals nationwide. The average age of patients was 50.7 years, 62.6% were male and 37.4% female. Most of the diagnosed respiratory conditions corresponded to the age group of 27-59 years (252 studies), the second most frequent corresponded to the group over 60 years, and the third to the group of 19-26 years. The most frequent findings of the radiologists/pneumologists were severe pneumonia, bilateral pneumonia with pleural effusion, bilateral pulmonary emphysema, diffuse ground glass opacity, hemidiaphragmatic paresis, calcified granuloma in the lower right lobe, bilateral pleural effusion, sequelae of tuberculosis, bilateral emphysema, and fibrotic changes, among others. Overall, an average of 86% agreement and 14% diagnostic discordance was determined between the two AI systems. The sensitivity of the AI system was 93% and the specificity 80% compared with RT-PCR.

Conclusion: Paraguay has an AI-based telemedicine screening system for the rapid stratified detection of COVID-19 from chest CT images of patients with respiratory conditions. This application strengthens the integrated network of health services, rationalizing the use of specialized human resources, equipment, and inputs for laboratory diagnosis.

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