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Ultrasonography

Ultrasonography

Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called...

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Updated: Jul 8, 2026

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

使用临床数据,超声波特征和深度学习的痛风综合风险预测模型:回顾性多中心研究

Lishan Xiao¹, Yizhe Zhao^2,3, Yuchen Li¹

¹Department of Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People's Republic of China.

Journal of inflammation research

|March 16, 2026

概括

一个新的综合模型整合了临床数据,超声波特征和深度学习预测,准确地预测了痛风风险. 这种方法增强了早期痛风检测和管理的诊断能力.

关键词:

第一个甲索 - 关节关节痛风是一种痛风.这个名字是名ogramogram.风险评估风险评估风险评估超声波学超声波学超声波学

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Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

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科学领域:

风湿病学和医学成像学
医疗保健中的人工智能

背景情况:

痛风预测模型传统上依赖于临床数据,往往缺乏准确性.
超声波 (美国) 功能为痛风病理生理学提供了新的见解.
深度学习 (DL) 在医学图像分析方面显示出前景.

研究的目的:

开发和验证一个用于预测痛风风险的综合模型.
将超声波功能和深度学习预测与临床数据相结合.
为量化个人痛风风险建立一个名谱.

主要方法:

对609名患者进行了第一次中关节 (MTP1) 关节的回顾性研究美国.
为美国图像分析开发DL模型.
后勤回归用于识别独立的风险因素并构建预测模型 (临床,美国,组合).

主要成果:

结合了临床数据 (性别,血清尿酸),美国特征 (托弗斯,双轮标志,骨质侵蚀) 和DL预测的综合模型实现了最高的性能.
内部测试队列 (ITC) 曲线下的面积 (AUC):0.904;外部测试队列 (ETC) AUC:0.881.
决策曲线分析 (DCA) 证实了组合名图的临床实用性.

结论:

结合临床,美国和DL数据的综合模型提供了强大的痛风风险预测.
一个基于七个预测因子 (性别,SUA,eGFR,托弗斯,骨质侵蚀,DCs,DL预测) 的诺米图量化了痛风风险.
这种综合方法提高了预测和管理痛风的能力.