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Chunk #6 — Materials and methods — Participants

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Predicting alcohol use disorder remission: a longitudinal multimodal multi-featured machine learning approach.
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The data consisted of 1376 participants (826 males and 550 females) from COGA, including EA and AA individuals. Data from seven collection sites were included in this study. The experimental protocols were approved by each site’s institutional review board, and informed consent (for those over 18 years of age) or assent (for those under 18 years of age) was obtained from all participants. Ascertainment and assessment procedures of COGA recruits have been described elsewhere22 and in Supplementary Materials. Only individuals who met criteria for lifetime DSM-5 AUD and who participated in at least two interviews were included in the sample for these analyses. We examined only participants who were diagnosed as DSM-5 AUD at their initial laboratory visit and reassessed years later, at a follow-up visit, when they were divided into two groups: (1) continued AUD: met criteria for active DSM-5 AUD at time 1 and time 2, and (2) remitted AUD: no longer met criteria for active DSM-5 AUD at time 2. The AUD and remission phenotypes were based on information from two consecutive interviews. Both continued AUD and