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The current diagnosis of AUD is mainly done manually by radiologists. This study proposes a novel computer\u2010vision\u2010based method for automatic detection of AUD based on wavelet Renyi entropy and three\u2010segment encoded Jaya algorithm from MRI scans. The wavelet Renyi entropy is proposed to provide multiresolution and multiscale analysis of features, describe the complexity of the brain structure, and extract the distinctive features. Grid search method was used to select the optimal wavelet decomposition level and Renyi order. The classifier was constructed based on feedforward neural network and a three\u2010segment encoded (TSE) Jaya algorithm providing parameter\u2010free training of the weights, biases, and number of hidden neurons. We have conducted the experimental evaluation on 235 subjects (114 are AUDs and 121 healthy). <jats:italic>k<\/jats:italic>\u2010fold cross validation has been used to avoid overfitting and report out\u2010of\u2010sample errors. The results showed that the proposed method outperforms four state\u2010of\u2010the\u2010art approaches in terms of accuracy. The proposed TSE\u2010Jaya provides a better performance, compared to the conventional approaches including plain Jaya, multiobjective genetic algorithm, particle swarm optimization, bee colony optimization, modified ant colony system, and real\u2010coded biogeography\u2010based optimization.<\/jats:p>","DOI":"10.1155\/2018\/3198184","type":"journal-article","created":{"date-parts":[[2018,1,17]],"date-time":"2018-01-17T23:32:08Z","timestamp":1516231928000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Identification of Alcoholism Based on Wavelet Renyi Entropy and Three\u2010Segment Encoded Jaya Algorithm"],"prefix":"10.1155","volume":"2018","author":[{"given":"Shui-Hua","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4055-7412","authenticated-orcid":false,"given":"Khan","family":"Muhammad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiding","family":"Lv","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9364-4686","authenticated-orcid":false,"given":"Yuxiu","family":"Sui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2491-7473","authenticated-orcid":false,"given":"Liangxiu","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4870-1493","authenticated-orcid":false,"given":"Yu-Dong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2018,1,17]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.11.034"},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2015.06.018"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2017.04.009"},{"key":"e_1_2_10_4_2","article-title":"Observed power and projected sample sizes to detect white matter atrophy in neuroimaging of alcohol use disorders","volume":"36","author":"Monnig M. 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