Artificial Intelligence in Renal Mass Characterization: A Systematic Review of Methodologic Items Related to Modeling, Performance Evaluation, Clinical Utility, and Transparency

Kocak Burak; Kaya Ozlem Korkmaz; Erdim Cagri; Kus Ece Ates; Kilickesmez Ozgur

首页> 外文期刊>AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences >Artificial Intelligence in Renal Mass Characterization: A Systematic Review of Methodologic Items Related to Modeling, Performance Evaluation, Clinical Utility, and Transparency

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Artificial Intelligence in Renal Mass Characterization: A Systematic Review of Methodologic Items Related to Modeling, Performance Evaluation, Clinical Utility, and Transparency

机译：肾小写的人工智能：系统审查与建模，绩效评估，临床效用和透明度相关的方法论项目

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摘要

OBJECTIVE. The objective of our study was to systematically review the literature about the application of artificial intelligence (AI) to renal mass characterization with a focus on the methodologic quality items.

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来源
《AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences》 |2020年第5期|共10页
作者
Kocak Burak; Kaya Ozlem Korkmaz; Erdim Cagri; Kus Ece Ates; Kilickesmez Ozgur;
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作者单位

Istanbul Training &

Res Hosp Dept Radiol TR-34098 Istanbul Turkey;

Koc Univ Koc Univ Hosp Dept Radiol Sch Med Istanbul Turkey;

Sultangazi Haseki Training &

Res Hosp Dept Radiol Istanbul Turkey;

Istanbul Training &

Res Hosp Dept Radiol TR-34098 Istanbul Turkey;

Istanbul Training &

Res Hosp Dept Radiol TR-34098 Istanbul Turkey;

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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
artificial intelligence (AI); machine learning; radiomics; renal cell carcinoma; renal mass;

机译：人工智能（AI）;机器学习;辐射瘤;肾细胞癌;肾肿块;

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Artificial Intelligence in Renal Mass Characterization: A Systematic Review of Methodologic Items Related to Modeling, Performance Evaluation, Clinical Utility, and Transparency

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