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Development of an AI Assessment System for Pediatric Respiratory Distress : A Prospective Study
Sponsor: Samsung Medical Center
Summary
This is a multicenter, prospective observational study designed to collect clinical data for the development of a vision-language model-based artificial intelligence system for automated assessment of pediatric respiratory patterns. The study enrolls pediatric patients aged 0 to 12 years who present to the pediatric emergency departments of participating institutions. Clinical and visual respiratory data are collected along with baseline clinical characteristics, including sex, age, body weight, height, presenting symptoms recorded at emergency department arrival, initial vital signs (body temperature, pulse rate, respiratory rate, blood pressure, and oxygen saturation), severity at presentation assessed by the Korean Triage and Acuity Scale (KTAS), emergency department management and outcomes such as hospital admission or discharge, and other relevant clinical information. These data are used for cohort characterization and for the development and evaluation of an AI-based system that aims to automatically analyze pediatric respiratory patterns and support objective respiratory assessment in pediatric emergency care.
Key Details
Gender
All
Age Range
0 Years - 12 Years
Study Type
OBSERVATIONAL
Enrollment
2200
Start Date
2025-10-28
Completion Date
2027-12
Last Updated
2026-03-20
Healthy Volunteers
No
Conditions
Locations (3)
CHA Bundang Medical Center, CHA University, 9, Yatap-ro, Bundang-gu
Seongnam-si, Gyeonggi-do, South Korea
Asan Medical Center, 88, Olympic-ro 43-gil, Songpa-gu
Seoul, Seoul, South Korea
Samsung Medical Center, 81, Irwon-ro, Gangnam-gu
Seoul, Seoul, South Korea