医学
腺癌
放射科
二元分类
人工智能
肺孤立结节
肺癌筛查
试验装置
癌症
计算机断层摄影术
内科学
计算机科学
支持向量机
作者
Zhengsong Pan,Ge Hu,Zhenchen Zhu,Weixiong Tan,Wei Han,Z.‐G. Zhou,Wei Song,Yizhou Yu,Lan Song,Zhengyu Jin
出处
期刊:Radiology
[Radiological Society of North America]
日期:2024-04-01
卷期号:311 (1): e232057-e232057
被引量:43
标识
DOI:10.1148/radiol.232057
摘要
Performance of deep learning models for predicting preinvasive, minimally invasive, or invasive adenocarcinoma was improved by combining binary and ternary classification models for predicting invasiveness and adjudication of discordant classification.
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