Ignite Creation Date:
2024-10-26 @ 3:37 PM
Last Modification Date:
2024-10-26 @ 3:37 PM
Study NCT ID:
NCT06542120
Status:
NOT_YET_RECRUITING
Last Update Posted:
None
First Post:
2024-08-04
Brief Title:
Research on Body Voice AI Recognition System for Childrens Health Management
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Intelligent Voice Model A New Paradigm Exploration for Child Health Management
Status:
NOT_YET_RECRUITING
Status Verified Date:
2024-04
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The purpose of this research is to develop a body voice artificial intelligence AI recognition device also referred to as an AI-assisted body sound identification device by utilizing a deep learning-based novel AI algorithm in conjunction with a big body voice model It could identify normal and abnormal heart breath and bowel sounds and to provide early screening and auxiliary diagnosis of congenital heart disease CHD respiratory infections diarrhea and other common multi-occurring diseases
Detailed Description:
The study employed a multicenter cross-sectional design The real-world data collected for this study included normal and definitively diagnosed heart sounds in children with congenital heart disease normal and definitively diagnosed respiratory tract infections in children with breath sounds specific cough sounds and normal and definitively diagnosed childrens bowel sounds with diarrhea The specialist team will carry out data governance annotation and feature sound extraction on the gathered normal and aberrant sounds in order to generate a superior multimodal training dataset Large model artificial intelligence algorithms deep learning machine learning etc are used to model and train the algorithm model of the body voice AI recognition device so that it can distinguish between normal and abnormal sound signals by AI The results of body sound AI identification will be compared with diagnostic reports from echocardiograms chest X-rays and belly X-rays in terms of AUC Area Under Curve score sensitivity specificity and accuracy to evaluate the impact of AI recognition devices on illness screening and supplementary diagnosis External validation will be conducted using homogeneous data from other sites This project aims to develop a new generation of intelligent sound auscultation instruments that could be used for early screening and auxiliary diagnosis of congenital heart disease respiratory infections diarrhea and other common multi-occurring diseases by utilizing large model artificial intelligence technologies
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None