ClinicalTrials.gov
public full text
Public Domain
Evaluate the Accuracy of a COPD Screening Algorithm Model
Chronic obstructive pulmonary disease (COPD) is one of the most common respiratory diseases. Early detection and treatment are critical to prevent the deterioration of COPD. In this study, we have established an algorithm that can detect and infer the severity of COPD from physiological parameters and audio data collected by wearable devices, and in this stage, we aim to evaluate the accuracy of this algorithm.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- An Observational Registry of Chinese COPD Study#841784
- Utilizing Wearable Device to Observe the Clinical Response of COPD Patients Treated With Combined Bronchodilator and Home-based Pulmonary Rehabilitation Program#994454
- A Study to Evaluate the Safety, Tolerability, Pharmacokinetics, and Dose-Response Relationship of Multiple Doses of GSK2269557 Administered as a Dry Powder to Chronic Obstructive Pulmonary Disease (COPD) Patients#878954
- Development of AECOPD Identification Tool (DETECT Study)#853393
- Validation of the C-mo System - Cough Monitoring#813097
Record · ID 833958
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive