首页> 外国专利> System, User Interface and Method For Interactive Negative Explanation of Machine learning Localization Models In Health Care Applications

System, User Interface and Method For Interactive Negative Explanation of Machine learning Localization Models In Health Care Applications

机译:医疗应用中机器学习定位模型交互式否定解释的系统、用户界面和方法

摘要

A method and system for assessing a machine learning model providing a prediction as to the disease state of a patient from a 2D or 3D image of the patient or a sample obtained therefrom. The machine learning model produces a prediction of the disease state from the image. The method involves presenting on a display of a workstation the image of the patient or a sample obtained therefrom along with a risk score or classification associated with the prediction. The image is further augmented with high-lighting to indicate one or more regions in the image which affected the prediction produced by the machine learning model. Tools are provided by which the user may highlight one or more regions of the image which the user deems to be suspicious for the disease state. Inference is performed on the user-highlighted areas by the machine learning model. The results of the inference are presented to the user via the display.
机译:一种用于评估机器学习模型的方法和系统,该机器学习模型从患者的2D或3D图像或从中获得的样本中预测患者的疾病状态。机器学习模型根据图像预测疾病状态。该方法涉及在工作站的显示器上显示患者的图像或从中获得的样本以及与预测相关的风险评分或分类。该图像进一步用高亮度增强,以指示图像中影响机器学习模型产生的预测的一个或多个区域。提供了一些工具,用户可以通过这些工具突出显示图像中用户认为对疾病状态可疑的一个或多个区域。机器学习模型对用户突出显示的区域进行推理。推理结果通过显示屏呈现给用户。

著录项

  • 公开/公告号US2022121330A1

    专利类型

  • 公开/公告日2022-04-21

    原文格式PDF

  • 申请/专利权人 GOOGLE LLC;

    申请/专利号US201917422356

  • 发明设计人 MARCIN SIENIEK;

    申请日2019-10-10

  • 分类号G06F3/0482;G16H50/30;G16H50/20;G06F3/0354;G06F3/04883;G06N3/08;G06N5/04;G06T7;

  • 国家 US

  • 入库时间 2022-08-25 00:35:25

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