ArticleAnalytical chemistry2026
Artificial Intelligence-Assisted Infrared Spectroscopy and Chemometrics for Enhanced Histopathology Screening of Micro- and Macrocancer Lesions.
Article in Analytical chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Accurate detection of micro- and macrocancer lesions remains a critical challenge in histopathology, as conventional hematoxylin and eosin staining requires labor-intensive analysis and is limited in sensitivity toward microscopic foci. Here, we present an artificial intelligence (AI)-assisted workflow integrating Fourier transform infrared (FT-IR) hyperspectral imaging with chemometric modeling for enhanced cancer screening in lung tissues. Using a focal-plane array (128 × 128 pixels with a pixel projection of 5.5 μm × 5.5 μm), hyperspectral maps were generated, enabling biochemical characterization of distinct morphological structures, including bronchial and vascular walls, parenchyma, and neoplastic regions. Histopathological annotations were employed to construct calibration data sets for noncancerous tissues, microcancer lesions, and macrocancer lesions. Discriminant analysis revealed high predictive accuracy across validation strategies, with CORRS-CV (δ = 5) outperforming conventional
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