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Comparison of Feature Selection Methods and Machine Learning Classifiers with Computed Tomography Radiomics-based Features for Predicting Chronic Obstructive Pulmonary Disease

Comparison of Feature Selection Methods and Machine Learning Classifiers with Computed Tomography Radiomics-based Features for Predicting Chronic Obstructive Pulmonary Disease
特征选择方法和机器学习分类器与基于计算机断层扫描放射组学特征的预测慢性阻塞性肺疾病的比较
批准号：
466971
负责人：
Makimoto Kalysta M
金额：
$1.27万
依托单位：
Toronto Metropolitan University
依托单位国家：
加拿大
项目类别：
Studentship Programs
财政年份：
2021
资助国家：
加拿大
项目状态：
已结题
起止时间：
2021-12-01 至 2022-12-01
来源：
https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=466971&lang=en
关键词：
Biophysics Biostatistics Chronic Obstructive Lung Disease Classification Feature Selection Imaging Machine Learning Radiomics Respiration Texture-Based Ct Features

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英文摘要
Radiomics is an image analysis technique that extracts numerical features from medical images, for example computed tomography (CT) images. These radiomic features can be used with machine learning models to predict outcomes. Machine learning models inclu
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Regional CT features for predicting rapid lung function decline in COPD
  • 批准号：
    495290
  • 项目类别：
  • 资助金额：
    $0.11万
  • 财政年份：
    2023
  • 负责人：
    Makimoto Kalysta M
  • 依托单位：
    Toronto Metropolitan University
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