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Feasibility of AI-based Classification of Normal, Wheeze and Crackle Sounds From Stethoscope in Clinical Settings

NCT05268263 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 60

Last updated 2023-04-06

No results posted yet for this study

Summary

Assessing the feasibility and testing the accuracy of the developed artificial intelligence algorithms for detection of wheezes and crackles in patients with lung pathologies in clinical settings on unseen local patient data acquired through three digital stethoscopes.

Conditions

Interventions

DEVICE

Artificial Intelligence Algorithm

The enrolled population will include patients with a history of lung pathologies. Artificial intelligence-based models are developed for classification of wheezes, crackles and normal lung sounds. These AI models will be tested and assessed on local lung sounds clinical data.

Sponsors & Collaborators

  • Lady Reading Hospital, Pakistan

    collaborator OTHER_GOV

  • NOABIO LLC

    collaborator UNKNOWN

  • Innova Smart Technologies (Pvt.) Ltd

    lead OTHER

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-01-06
Primary Completion
2022-02-22
Completion
2022-02-22
FDA Device
Yes

Countries

  • Pakistan

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05268263 on ClinicalTrials.gov