CG-RecNet: a gated and attention-fused deep learning framework for label-free classification of neural stem cell differentiation via imaging flow cytometry

Grad-CAM analysis indicates that the model's attention aligns with biologically relevant hallmarks, such as neurite outgrowth and soma texture. CG-RecNet provides a reliable, non-invasive, and qualitatively interpretable tool for neural stem cell research.