NCT06542120

Research on Body Voice AI Recognition System for Children's Health Management

Intelligent Voice Model: A New Paradigm Exploration for Child Health Management

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 30,000 (estimated)
• Sponsor: Xinhua Hospital, Shanghai Jiao Tong University School of Medicine · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

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 children's 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.

Conditions

• Congenital Heart Disease
• Bronchopneumonia
• Abdominal Disease

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Heart Auscultation and Echocardiography	Heart auscultation will be done by pediatrician and echocardiography by echocardiologist
DIAGNOSTIC_TEST	Chest Auscultation and Chest imaging examinations	Chest auscultation will be done by pediatrician and chest imaging examinations by radiologist
DIAGNOSTIC_TEST	Abdominal Auscultation and Abdominal imaging examinations	Abdominal auscultation will be done by pediatrician and chest imaging examinations by radiologist

Timeline

• Start date: 2024-08-21
• Primary completion: 2025-07-31
• Completion: 2025-12-30
• First posted: 2024-08-07
• Last updated: 2024-08-07

Locations

5 sites across 1 country: China