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Interpretable machine learning models improve prediction of tumor features in stage IA lung adenocarcinoma, indicating better surgical outcomes.
An interpretable KNN model was successfully developed to predict the presence of MP/S components in stage IA LUAC patients, demonstrating superior predictive performance. Accurate evaluation of relevant tumor characteristics possesses substantial clinical significance, as it enables guidance on the optimization of surgical approaches to enhance patient prognosis.
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Li et al. (2025) studied this question.
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