Identification of smokingstatus from routine blood test results using deep neural network analysis.
N. Skjodt (Lethbridge, Canada), P. Mamoshina (Baltimore, United States of America), K. Kochetov (Baltimore, United States of America), F. Cortese (Boston, United States of America), A. Kovalchuk (Lethbridge, Canada), A. Aliper (Baltimore, United States of America), E. Putin (Baltimore, United States of America), M. Scheibye-Knudsen (Copenhagen, Denmark), C. Cantor (Boston, United States of America), A. Zhavoronkov (Baltimore, United States of America), O. Kovalchuk (Lethbridge, Canada)
Source: International Congress 2018 – Novel findings in biomarkers of tobacco use, exposure, hazards and genetics
Disease area: Airway diseases
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N. Skjodt (Lethbridge, Canada), P. Mamoshina (Baltimore, United States of America), K. Kochetov (Baltimore, United States of America), F. Cortese (Boston, United States of America), A. Kovalchuk (Lethbridge, Canada), A. Aliper (Baltimore, United States of America), E. Putin (Baltimore, United States of America), M. Scheibye-Knudsen (Copenhagen, Denmark), C. Cantor (Boston, United States of America), A. Zhavoronkov (Baltimore, United States of America), O. Kovalchuk (Lethbridge, Canada). Identification of smokingstatus from routine blood test results using deep neural network analysis.. 3814
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