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Creating and Assessing a Voice Dataset for Automated Classification of Chronic Obstructive Pulmonary Disease

Chronic Obstructive Pulmonary Disease Clinical Trial

Official title:
Creating and Assessing a Voice Dataset for Automated Classification of Chronic Obstructive Pulmonary Disease

Clinical Trial Summary

This work aims to evaluate whether voice recordings collected from patients diagnosed with COPD and healthy control groups can be used to detect the disease using machine learning techniques.

Clinical Trial Description

Voice data and sociodemographic data on gender and age will be collected through the "VoiceDiganostic" application from the company Voice Diagnostic, which allows one to participate without location dependency. Participants with a diagnosis will be marked as the COPD group, and others will be marked as the healthy control group. Private information such as known comorbidities, personal security numbers, health parameters and communication information will be separately noticed in a participation table for each group. The collected data 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 further usage as an input to ML techniques. 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. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT05897944
Study type Observational
Source Blekinge Institute of Technology
Contact
Status Active, not recruiting
Phase
Start date December 16, 2021
Completion date December 30, 2023
View Details
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