A New Machine Learning Framework for Understanding the Link Between Cannabis Use and First-Episode Psychosis.
AuthorAlghamdi, W; Stamate, D; Stahl, D; Zamyatin, A; Murray, R; Di Forti, M
Source TitleStud Health Technol Inform
University of Melbourne Author/sMurray, Robin
AffiliationClinical School (Austin Health)
Document TypeConference Proceeding
CitationsAlghamdi, W; Stamate, D; Stahl, D; Zamyatin, A; Murray, R; Di Forti, M, A New Machine Learning Framework for Understanding the Link Between Cannabis Use and First-Episode Psychosis., Stud Health Technol Inform, 2018, 248 pp. 9 - 16
Access StatusOpen Access
Lately, several studies started to investigate the existence of links between cannabis use and psychotic disorders. This work proposes a refined Machine Learning framework for understanding the links between cannabis use and 1st episode psychosis. The novel framework concerns extracting predictive patterns from clinical data using optimised and post-processed models based on Gaussian Processes, Support Vector Machines, and Neural Networks algorithms. The cannabis use attributes' predictive power is investigated, and we demonstrate statistically and with ROC analysis that their presence in the dataset enhances the prediction performance of the models with respect to models built on data without these specific attributes.
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