https://www.selleckchem.com/products/wm-8014.html
79, an OR of 7.4 and a sensitivity of 27.9% at the same specificity. The machine-learning model was more accurate than standard eligibility criteria for lung cancer screening and more accurate than the modified PLCOm2012 model when applied to a screening-eligible population. Influential model variables included known risk factors and novel predictors such as white blood cell and platelet counts. A machine-learning model was more accurate for early diagnosis of NSCLC than either standard eligibility criteria for screening or the modified
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