Finds automated detection enhances diagnosis accuracy of STAS in NSCLC, suggesting AI's role in pathology.
< .05). We propose a deep learning-based artificial intelligence framework for automated STAS detection and quantification in digital whole-slide images of NSCLC. This model holds promising potential to assist pathologists in achieving more comprehensive and accurate diagnosis of STAS.
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Zhang et al. (2026) studied this question.
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