Suppr超能文献

基于 CT 影像组学的 COVID-19 患者预后预测模型研究。

Study on the prognosis predictive model of COVID-19 patients based on CT radiomics.

机构信息

Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Harbin, Heilongjiang Province, China.

Department of Research Collaboration, R&D center, Beijing Deepwise & League of PHD Technology Co., Ltd, Beijing, China.

出版信息

Sci Rep. 2021 Jun 2;11(1):11591. doi: 10.1038/s41598-021-90991-0.

Abstract

Making timely assessments of disease progression in patients with COVID-19 could help offer the best personalized treatment. The purpose of this study was to explore an effective model to predict the outcome of patients with COVID-19. We retrospectively included 188 patients (124 in the training set and 64 in the test set) diagnosed with COVID-19. Patients were divided into aggravation and improvement groups according to the disease progression. Three kinds of models were established, including the radiomics, clinical, and combined model. Receiver operating characteristic curves, decision curves, and Delong's test were used to evaluate and compare the models. Our analysis showed that all the established prediction models had good predictive performance in predicting the progress and outcome of COVID-19.

摘要

及时评估 COVID-19 患者的疾病进展有助于提供最佳的个性化治疗。本研究旨在探索一种有效的模型来预测 COVID-19 患者的结局。我们回顾性纳入了 188 例确诊为 COVID-19 的患者(训练集 124 例,测试集 64 例)。根据疾病进展,患者被分为加重组和改善组。建立了三种模型,包括放射组学、临床和联合模型。使用接受者操作特征曲线、决策曲线和 Delong 检验来评估和比较模型。我们的分析表明,所有建立的预测模型在预测 COVID-19 的进展和结局方面均具有良好的预测性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e85/8172890/c829ce0b66e0/41598_2021_90991_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验