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Updated: Jul 12, 2026

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PACS集成的机器学习乳腺密度分类器:临床验证

John Lewin1, Sven Schoenherr2, Martin Seebass2

  • 1Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States of America.

Clinical imaging
|July 8, 2023
PubMed
概括

一个新的人工智能工具准确地评估了乳房密度,显示了与放射科医生的高度一致. 这种机器学习模型预测了乳腺成像报告和数据系统 (BI-RADS) 的密度类别,有助于乳房图像分析.

关键词:
人工智能的人工智能是人工智能.乳腺密度 乳腺密度乳房学 乳房学 乳房学

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相关概念视频

Aggregates Classification01:29

Aggregates Classification

Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...