An observational study in Congenital Heart Disease, Bronchopneumonia and Abdominal Disease, sponsored by Xinhua Hospital, Shanghai Jiao Tong University School of Medicine. Recruiting at 5 sites in China. Open to participants aged Up to 18 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-08-12.
Sponsored by Xinhua Hospital, Shanghai Jiao Tong University School of Medicine · Observational
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.
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.
991 studies on the registry are indexed under Heart Defects, Congenital; 251 are open to participants now.
This study's planned enrollment of 30,000 is above the median of 119 across 440 observational studies indexed under Heart Defects, Congenital.
Browse Heart Defects, Congenital studies →Xinhua Hospital, Shanghai Jiao Tong University School of Medicine is the lead sponsor of 225 studies on the registry; 55 are open to participants now.
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You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Age range: 0 to 18 years old, with no gender restriction. Children who have been diagnosed with congenital heart disease (CHD) or confirmed to be free of CHD through echocardiographic examinations. Children who have been diagnosed with bronchopneumonia or confirmed to be free of bronchopneumonia through chest imaging examinations. Children who have been diagnosed with abdominal diseases or confirmed to be free of abdominal diseases through abdominal imaging examinations.
Diagnostic Test: Heart Auscultation and Echocardiography · Diagnostic Test: Chest Auscultation and Chest imaging examinations · Diagnostic Test: Abdominal Auscultation and Abdominal imaging examinations
Heart auscultation will be done by pediatrician and echocardiography by echocardiologist
Chest auscultation will be done by pediatrician and chest imaging examinations by radiologist
Abdominal auscultation will be done by pediatrician and chest imaging examinations by radiologist
Sensitivity
Sensitivity in CHD, lung disease and abdominal screening by different artificial intelligence algorithm and auscultation
Time frame: 1 month
Specificity
Specificity in CHD, lung disease and abdominal screening by different artificial intelligence algorithm and auscultation
Time frame: 1 month
AUC
AUC in CHD, lung disease and abdominal screening by different artificial intelligence algorithm and auscultation
Time frame: 1 month
Started May 2024 (actual). Primary completion is estimated for Dec 2026, 31 months after the start.
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Xinhua Hospital, Shanghai Jiao Tong University School of Medicine →