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A machine learning approach to identify drivers of e-cigarette dependence Nominated Principal Investigator Michael Chaiton Independent Scientist, Centre for Addiction and Mental Health [email protected] Knowledge User Peter Selby Centre for Addiction and Mental Health Co-investigators Susan J Bondy Adam G Cole Tara E Elton-Marshall Hayley A Hamilton Sean Hill Scott Leatherdale Nikolaos Mitsakakis Robert M Schwartz Wei Wang Project Summary Understanding person-level drivers of current e-cigarette use (vaping) is crucial to guide tobacco policy, but prior studies have not fully identified these drivers due to the reliance on cross-sectional data, small sample sizes in many studies, lack of generalizability, and limitations of traditional data analyses

In this disorder, the bronchioles compress and narrow due to the formation of scar tissue, greatly diminishing the breathing capacity of people with the disorder

ISBN 978-1857800913

Most local AQI scales (like the US EPAs) are set by national governments

It wont make the cigar taste brand new, but it can noticeably smooth the re-entry