Research on Body Voice AI Recognition System for Children's Health Management
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
AgeUp to 18
SponsorXinhua Hospital, Shanghai Jiao Tong University School of Medicine
About this trial
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.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Age 0~18 years old, gender is not limited
Children who have been diagnosed with congenital heart disease by cardiac ultrasound or who do not have congenital heart disease
Children diagnosed with bronchopneumonia or without bronchopneumonia
Children who are clinically diagnosed with intestinal diseases or who do not suffer from intestinal diseases
Disqualifiers
≥ 18 years old
Children who are unable to undergo cardiac ultrasound, chest imaging or other related examinations
Subjects who are unable to obtain informed consent, or who are unwilling to cooperate with the provision of diagnosis and treatment related data for further analysis and research as required by the study.
Trial population
1. Children (0-18 years old) with congenital heart disease confirmed by cardiac ultrasound and children without congenital heart disease confirmed by cardiac ultrasound. 2. Children (0-18 years old) with bronchopneumonia confirmed by chest imaging examination and children without bronchopneumonia confirmed by imaging. 3. Children (0-18 years old) with abdominal imaging confirmed abdominal disease and children diagnosed without abdominal disease by imaging.
Trial design
Design model
Cohort
Time perspective
Cross-sectional
Treatments tested in this trial
Heart Auscultation and Echocardiography
Diagnostic testHeart auscultation will be done by pediatrician and echocardiography by echocardiologist
Chest Auscultation and Chest imaging examinations
Diagnostic testChest auscultation will be done by pediatrician and chest imaging examinations by radiologist
Abdominal Auscultation and Abdominal imaging examinations
Diagnostic testAbdominal auscultation will be done by pediatrician and chest imaging examinations by radiologist
Treatment groups
30,000 Participants
are divided into 1 treatment groupGroup A: 0 ~ 18 years old children3 interventions
Trial outcomes
Primary outcomes
1
Sensitivity
Sensitivity in CHD, lung disease and abdominal screening by different artificial intelligence algorithm and auscultation
Time frame
1 month2
Specificity
Specificity in CHD, lung disease and abdominal screening by different artificial intelligence algorithm and auscultation
Time frame
1 month3
AUC
AUC in CHD, lung disease and abdominal screening by different artificial intelligence algorithm and auscultation
Time frame
1 monthSponsors and contacts
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Source ClinicalTrials.gov