您也可能阅读
通过共同作者、期刊和引用图与本文相关的文章。
Weijia Fan1, Qixuan Chen1, Valerie Maccarrone2
1Department of Biostatistics, Mailman School of Public Health Columbia University, 722 st 168th Street, New York, NY 10032, United States of America.
机器学习有助于通过识别关键放射性特征来诊断肺纤维化模式. 使用贝叶斯增量回归树的在线应用程序协助放射科医生,提高诊断准确度.
07:53Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
Published on: October 13, 2023
08:05Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
科学领域:
背景情况:
研究的目的:
主要方法:
主要成果:
结论: