Author(s)

XiangMeng Shu

Affiliation(s)

School of Computer Science, Xi'an Shiyou University, Xi'an 710065, Shaanxi, China.

Corresponding Author

XiangMeng Shu

ABSTRACT

Determining the optimal timing for non-invasive prenatal testing (NIPT) is critical, as it requires balancing the need for early detection with ensuring sufficient fetal DNA concentration for accuracy, particularly in male pregnancies. This study aims to optimize the NIPT window by analyzing the correlation between fetal Y chromosome concentration and maternal factors (gestational age and BMI) and proposing a stratified testing strategy. We first employed a Generalized Additive Mixed Model (GAMM) to capture complex nonlinear relationships, revealing a gradual increase in concentration with gestational age and a nonlinear inflection effect for BMI (with a slowdown after BMI~30). Subsequently, a hierarchical refinement strategy was implemented: pregnant women were clustered into homogeneous groups based on BMI and time-to-target concentration. A risk function quantifying both temporal and accuracy risks was then minimized using a simulated annealing algorithm to identify the optimal gestational week for each cluster. Results indicate that clusters with a BMI around 30 are suitable for early testing at 11 weeks, while high-BMI clusters require postponement to 24-25 weeks. This stratified approach significantly improved expected accuracy, with one group achieving 100%. The key innovations lie in using an interpretable GAMM for nonlinear analysis, data-driven clustering for population stratification, and a simulated annealing framework for balanced timing optimization.

KEYWORDS

Chromosomal concentration; Generalized additive mixture model; Clustering; Simulated annealing; Optimal timing

CITE THIS PAPER

XiangMeng Shu. A fine-tuned study on optimal timing for non-invasive prenatal testing based on generalized additive mixed models and simulated annealing optimization. World Journal of Information Technology. 2025, 3(6): 1-9. DOI: https://doi.org/10.61784/wjit3070.

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