Stamate, Daniel; Alghamdi, Wajdi; Stahl, Daniel; Zamyatin, Alexander; Murray, Robin and di Forti, Marta. 2018. 'Can Artificial Neural Networks Predict Psychiatric Conditions Associated with Cannabis Use?'. In: 14th AIAI: IFIP International Conference on Artificial Intelligence Applications and Innovations. Rhodes, Greece. [Conference or Workshop Item]

Stamate, Daniel; Alghamdi, Wajdi; Stahl, Daniel; Pu, Ida; Murtagh, Fionn; Belgrave, Danielle; Murray, Robin and di Forti, Marta. 2018. 'Predicting First-Episode Psychosis Associated with Cannabis Use with Artificial Neural Networks and Deep Learning'. In: IPMU 2018: 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Cadiz, Spain. [Conference or Workshop Item]

Walghamdi, Wajdi; Stamate, Daniel; Stahl, Daniel; Murray, Robin and Di Forti, Marta. 2018. 'A New Machine Learning Framework for Understanding the Link between Cannabis Use and First-Episode Psychosis'. In: Proceedings of the 12th eHealth Conference. Vienna, Austria. [Conference or Workshop Item]

Ajnakina, Olesya; Lally, John; Di Forti, Marta; Stilo, Simona; Kolliakou, Anna; Gardner-Sood, Poonam; Dazzan, Paola; Pariante, Carmine; Marques, Tiago Reiss; Mondelli, Valeria; MacCabe, James; Gaughran, Fiona; David, Anthony S; Stamate, Daniel; Murray, Robin and Fisher, Helen L.. 2018. Utilising symptom dimensions with diagnostic categories improves prediction of time to first remission in first-episode psychosis. Schizophrenia Research, 193, pp. 391-398. ISSN 0920-9964 [Article]

Bramon, Elvira; McDonald, Colm; Croft, Rodney J.; Landau, Sabine; Filbey, Francesca; Gruzelier, John; Sham, Pak; Frangou, Sophia and Murray, Robin. 2005. Is the P300 wave an endophenotype for schizophrenia? A meta-analysis and a family study. NeuroImage, 27(4), pp. 960-968. ISSN 10538119 [Article]

Bramon, Elvira; Croft, Rodney J.; McDonald, Colm; Virdi, Gurkamal; Gruzelier, John; Baldeweg, Torsten; Sham, Pak; Frangou, Sophia and Murray, Robin. 2004. Mismatch negativity in schizophrenia: a family study. Schizophrenia Research, 67(1), pp. 1-10. ISSN 09209964 [Article]