ArticleACS pharmacology & translational science2025
Infrared Imaging Combined with Machine Learning for Detection of the (Pre)Invasive Pancreatic Neoplasia.
Article in ACS pharmacology & translational science, 2025. 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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6 authors.
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Abstract
With the challenge of limited early stage detection and a resulting five-year survival rate of only 13%, pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal cancers. Replacing the high-cost and time-consuming grading of pancreatic samples by pathologists with automated diagnostic approaches can revolutionize PDAC detection and thus accelerate patient admission into the clinical setting for treatment. To address this unmet diagnostic need and facilitate the shift of tissue screening toward automated systems, we combined stain-free histology-specifically, Fourier-transform infrared (FT-IR) imaging-with machine learning. The obtained stain-free model was trained to distinguish between normal, benign, and malignant areas in analyzed specimens using hematoxylin and eosin stained pancreatic tissues isolated from KC (Kras
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Registered trials
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