@inbook{45e1aff75acd4479b1bf885eae59f437,
title = "A new machine learning framework for understanding the link etween cannabis use and first-episode psychosis",
abstract = "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.",
keywords = "eHealth, First-episode psychosis, Gaussian processes, Machine learning, Neural networks, Support vector machine",
author = "Wajdi Alghamdi and Daniel Stamate and Daniel Stahl and Alexander Zamyatin and Robin Murray and {Di Forti}, Marta",
year = "2018",
month = jan,
day = "1",
doi = "10.3233/978-1-61499-858-7-9",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "9--16",
booktitle = "Health Informatics Meets eHealth",
note = "12th Annual Conference on Health Informatics Meets eHealth, eHealth 2018 ; Conference date: 08-05-2018 Through 09-05-2018",
}