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相关概念视频

Histogram01:05

Histogram

The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
A histogram graph consists of contiguous (adjoining) boxes. The heights of the bars correspond to frequency values. The graph will have the same shape with respective labels. The...

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相关实验视频

Updated: Jun 28, 2026

High-Throughput, Multi-Image Cryohistology of Mineralized Tissues
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HistoMIL:一个Python包,用于在组织病理学幻灯片上训练多个实例学习模型.

Shi Pan1, Maria Secrier1

  • 1Department of Genetics, Evolution and Environment, UCL Genetics Institute, University College London, London WC1E 6BT, UK.

iScience
|October 20, 2023
PubMed
概括
此摘要是机器生成的。

HistoMIL简化了分析组织病理学幻灯片的深度学习,使得精确的癌症基因预测成为可能. 该工具帮助计算病理学家和研究人员使用多实例学习算法进行疾病诊断.

关键词:
人工智能的人工智能是人工智能.历史学 历史学 历史学机器学习 机器学习

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科学领域:

  • 计算病理学计算病理学
  • 生物医学信息学是生物医学信息学.
  • 机器学习在医疗保健中的应用

背景情况:

  • 血素和乙素 (H&E) 染色的幻灯片对于疾病诊断至关重要.
  • 深度学习的进步使得在组织病理学中能够检测到复杂的分子模式.
  • 多个实例学习 (MIL) 对自动化分析有希望,但实施起来很复杂.

研究的目的:

  • 介绍HistoMIL,这是一个Python包,简化了用于计算病理学的MIL算法实现.
  • 为研究人员和病理学家提供基于MIL的算法的培训和推断.
  • 为功能编码,转移学习和MIL算法应用提供一个集成的管道.

主要方法:

  • 开发了HistoMIL,这是一个使用PyTorch Lightning进行定制的Python包.
  • 集成了一个自我监督的学习模块,用于功能编码.
  • 实施了一个管道,包括转移学习 (TL) 和三个MIL算法:ABMIL,DSMIL和TransMIL.

主要成果:

  • 使用乳腺癌组织学幻灯片,HistoMIL成功构建了2487个癌症标志基因的预测模型.
  • 在基因预测任务中,接收器操作特征曲线 (AUROC) 下实现的区域性能高达85%.
  • 证明了该软件包在简化复杂的MIL算法工作流程方面的能力.

结论:

  • 在计算病理学中,HistoMIL显著简化了先进的MIL算法的应用.
  • 该套餐使研究人员和病理学家能够利用深度学习来加强疾病诊断和分子模式检测.
  • HistoMIL促进了从组织病理学数据的预测模型的开发,推进了精准医学.