AI for Newborn Metabolic Screening
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About
The goal of this clinical trial is to evaluate whether an artificial intelligence (AI)-based interpretation system can accurately diagnose inherited metabolic disorders in newborns undergoing routine screening. The main questions it aims to answer are:
What is the sensitivity and specificity of the AI system compared to standard manual interpretation? Does the AI system reduce variability in screening results? Researchers will compare the AI interpretation results with those from standard manual review by trained laboratory staff to assess diagnostic performance.
Participants will:
Have their routine newborn screening blood samples analyzed using both the AI system and standard manual interpretation Be followed according to national newborn screening guidelines if either method indicates a positive result
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
- Newborns who underwent routine newborn screening for inherited metabolic disorders at the Zhejiang Provincial Newborn Screening Center between May 2025 and December 2027
- Blood samples collected between 2 and 28 days of age
- Availability of complete newborn screening test data and essential clinical information
Exclusion criteria
- Missing, incomplete, or poor-quality screening data
- Duplicate samples from the same newborn
Trial design
Primary purpose
Allocation
Interventional model
Masking
200,000 participants in 1 patient group
Trial contacts and locations
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Central trial contact
Hu, PhD
Data sourced from clinicaltrials.gov
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