Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield

Hassanpour Saeed; Langlotz Curtis P.; Amrhein Timothy J.; Befera Nicholas T.; Lungren Matthew P.

首页> 外文期刊>AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences >Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield

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Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield

机译：两种大型学术放射学实践膝关节MRI报告机器学习分类器的性能：一种估算诊断产量的工具

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摘要

OBJECTIVE. The purpose of this study is to evaluate the performance of a natural language processing (NLP) system in classifying a database of free-text knee MRI reports at two separate academic radiology practices.

机译：客观的。本研究的目的是评估自然语言处理（NLP）系统在分类自由文本膝关节MRI报告数据库中的两个单独学术放射学惯例。

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来源
《AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences》 |2017年第4期|共4页
作者
Hassanpour Saeed; Langlotz Curtis P.; Amrhein Timothy J.; Befera Nicholas T.; Lungren Matthew P.;
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作者单位

Stanford Univ Stanford Ctr Biomed Informat Res Stanford CA 94305 USA;

Stanford Univ Med Ctr Sch Med Dept Radiol 725 Welch Rd Rm 1675 Stanford CA 94305 USA;

Duke Univ Med Ctr Dept Radiol Durham NC USA;

Duke Univ Med Ctr Dept Radiol Durham NC USA;

Stanford Univ Med Ctr Sch Med Dept Radiol 725 Welch Rd Rm 1675 Stanford CA 94305 USA;

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原文格式 PDF
正文语种 eng
中图分类放射医学;
关键词
classification; machine learning; MRI;

机译：分类;机器学习;MRI;

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1. Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield [J] . Hassanpour Saeed, Langlotz Curtis P., Amrhein Timothy J., AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences . 2017,第4期

机译：两种大型学术放射学实践膝关节MRI报告机器学习分类器的性能：一种估算诊断产量的工具
2. Local staging with multiparametric MRI in daily clinical practice: diagnostic accuracy and evaluation of a radiologic learning curve [J] . Jansen B. H. E., Oudshoorn F. H. K., Tijans A. M., World journal of urology . 2018,第9期

机译：日常临床实践中的多次MRI当地分期：诊断准确性和放射学学习曲线的评估
3. Developing Classifiers through Machine Learning Algorithms for Student Placement Prediction Based on Academic Performance [J] . Maurya Laxmi Shanker, Hussain Md Shadab, Singh Sarita Applied Artificial Intelligence . 2021,第5a8期

机译：基于学术表现的学生放置预测，通过机器学习算法开发分类器
4. Attention-Based Explanation in a Deep Learning Model For Classifying Radiology Reports [C] . Luca Putelli, Alfonso E. Gerevini, Alberto Lavelli, International Conference on Artificial Intelligence in Medicine . 2021

机译：基于关注的放射学报告深层学习模型的解释
5. Using Machine Learning Tools to Predict the Severity of Osteoarthritis Based on Knee X-Ray Data [D] . Xiao, Yaorong. 2020

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6. A Comparative Systematic Literature Review on Knee Bone Reports from MRI X-Rays and CT Scans Using Deep Learning and Machine Learning Methodologies [O] . Hafsa Khalid, Muzammil Hussain, Mohammed A. Al Ghamdi, 2020

机译：利用深层学习和机器学习方法对MRIX射线和CT扫描的膝关节骨报告进行比较系统文献综述
7. A Comparative Systematic Literature Review on Knee Bone Reports from MRI, X-Rays and CT Scans Using Deep Learning and Machine Learning Methodologies [O] . Hafsa Khalid, Muzammil Hussain, Mohammed A. Al Ghamdi, 2020

机译：利用深层学习和机器学习方法对MRI，X射线和CT扫描的膝关节骨报告进行比较系统文献综述

Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield

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