Spectroscopic Quantification of Plasma Free Hemoglobin Based on Paired Domain Adaptation and Orthogonality Constraints

ABSTRACT Objective We propose a paired domain‐adaptation deep regression method for multi‐pathlength spectroscopy to quantify plasma free hemoglobin (FHB) robustly across measurement conditions. Methods UV–Vis–NIR spectra (300–1160 nm; 945 wavelengths) were acquired using an Avantes spectrometer, with five optical pathlengths per sample. Spectra were preprocessed by standard normal variate (SNV), and labels were log‐transformed (log (1 + y )) to mitigate long‐tailed instability. The network integrates domain–path affine calibration, a 1D‐CNN encoder, and attention‐based multi‐path fusion, followed by shared–private feature disentanglement. A paired consistency loss aligns only the shared representation across paired domains, and an orthogonality constraint encourages domain‐specific separation. Performance was evaluated via regression‐stratified five‐fold cross‐validation using RMSE and R 2 on the raw scale. Results For N = 251 samples, λ pair = 1.0 achieved RMSE = 260.53 ± 62.01 and R 2 = 0.748 ± 0.088. Conclusion The method improves cross‐domain robustness and interpretability for plasma FHB prediction.