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Machine Learning for Flow Cytometry Clinical Data and Trial Analysis

Machine Learning for Flow Cytometry Clinical Data and Trial Analysis
用于流式细胞术临床数据和试验分析的机器学习
批准号:
410311
负责人:
Brinkman Ryan
金额:
$23.13万
依托单位国家:
加拿大
项目类别:
Operating Grants
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-09-01 至 2021-07-01

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中文摘要
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英文摘要
Flow cytometry (FCM) is the predominant technique used to identify and quantify the widest variety of cell types. It plays critical roles in the characterization and diagnosis of cancer, blood diseases, and immune system disorders by basic researchers, cl
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Automated analysis of big flow cytometry data.
  • 批准号:
    352911
  • 项目类别:
    Operating Grants
  • 资助金额:
    $9.56万
  • 财政年份:
    2016
  • 负责人:
    Brinkman Ryan
  • 依托单位:
Statistical analysis of clinical lymphoma data for automated quality assurance of diagnosis and biomarker identification
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis