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In This Study, the Sponsor Would Like to Collaborate with Institution and Investigator to Aggregate Participants Data and to Pilot Its Software Algorithm Using Machine Learning and Threshold Based Methods for Predicting Exacerbations and Deterioration Within a 60 Days Period Post-discharge
Sponsor: Respiree Pte Ltd
Summary
In this study, the sponsor would like to collaborate with Institution and Investigator to aggregate participants data and to pilot its software algorithm using machine learning and threshold based methods for predicting exacerbations and deterioration within a 60 days period post-discharge.
Official title: Software Algorithm Using Machine Learning and Threshold Based Methods for Predicting Exacerbations and Deterioration
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
20
Start Date
2025-03-01
Completion Date
2025-07-01
Last Updated
2025-01-29
Healthy Volunteers
No
Conditions
Interventions
A non-invasive cardio-respiratory sensor will be applied on the subjects to measure parameters to identify exacerbations
This Study aims to pilot software algorithms based on respiratory features and hemodynamics for predicting exacerbations on a total of 20 participants with COPD. The end-points of this Study includes the following: 1. To validate respiratory-based biomarkers in models to predict exacerbations - benchmarking to be done versus physician assess exacerbations, emergency department visits, hospitalizations and any other visit. 2. To validate level of compliance, drop-out rate and if additional measures are required to get participants to follow-on