Vowel Segmentation for Classification of Chronic Obstructive Pulmonary Disease Using Machine Learning
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- 入组人数
- 68
- 试验地点
- 1
- 主要终点
- Classification performance
研究概览
简要总结
This work aims to evaluate whether the segmentation of vowel recordings collected from patients diagnosed with COPD and healthy control groups can increase the classification precision of machine learning techniques.
详细描述
Voice data and sociodemographic data on gender and age will be collected through the "VoiceDiganostic" application from the company Voice Diagnostic. Collected vowel recordings will be segmented and tested to determine whether some segments contain more information for the discrimination of COPD from healthy control groups.
Each segment will be transformed into mathematical vocal measures called voice features. A dataset consisting of voice features in conjunction with demographics and health data will be constructed for each segment which in turn will be evaluated for classification performance using several machine learning algorithms.
Descriptive statistical analysis will be held on attributes containing information on input data and gained outcomes from ML algorithms. The achieved results will be presented in the form of summary tables and graphs.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •being 18 years old and older.
排除标准
- •being under 18 years old and older.
结局指标
主要结局
Classification performance
时间窗: 30 weeks
Binary classification performance of the ML algorithm on each segment.
次要结局
未报告次要终点