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Thus, a collective screening of these smokers will expose the 85% of the same risk for harm. Future studies should develop and test risk prediction models, including those based on machine learning or artificial intelligence, to identify smokers who are likely to develop lung cancer so that they can be selected for screening to optimize the risk-benefit ratio of such screening, Faselis added

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Critics of mainstream tobacco controlwhich tends to favor prohibition-centered measures on lower-risk productspoint to Japan as a potential model for nations around the world

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Smoking Accelerates Atrioventricular Conduction in Humans Concordant with Increased Dopamine Release