Shamsutdinova, Diana; Stamate, Daniel and Stahl, Daniel. 2025. Balancing accuracy and Interpretability: An R package assessing complex relationships beyond the Cox model and applications to clinical prediction. International Journal of Medical Informatics, 194, 105700. ISSN 1386-5056 [Article]

Reeves, David; Morgan, Catharine; Stamate, Daniel; Ford, Elizabeth; Ashcroft, Darren M.; Kontopantelis, Evangelos; Van Marwijk, Harm and McMillan, Brian. 2024. Identifying individuals at high risk for dementia in primary care: Development and validation of the DemRisk risk prediction model using routinely collected patient data. PLoS ONE, 19(10), e0310712. ISSN 1932-6203 [Article]

Musto, Henry; Stamate, Daniel; Logofatu, Doina and Stahl, Daniel. 2024. 'Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling'. In: Artificial Neural Networks and Machine Learning – ICANN 2024. Lugano, Switzerland 17 - 20 September 2024. [Conference or Workshop Item]

Stamate, Daniel; Davuloori, Pradyumna; Logofatu, Doina; Mercure, Evelyne; Addyman, Caspar and Tomlinson, Mark. 2024. 'Ensembles of Bidirectional LSTM and GRU Neural Nets for Predicting Mother-Infant Synchrony in Videos'. In: Engineering Applications of Neural Networks: 25th International Conference on Engineering Applications of Neural Networks (EANN 2024). Corfu, Greece 27 - 30 June 2024. [Conference or Workshop Item]

Musto, Henry; Stamate, Daniel; Logofatu, Doina and Ouarbya, Lahcen. 2024. 'On a Survival Gradient Boosting, Neural Network and Cox PH Based Approach to Predicting Dementia Diagnosis Risk on ADNI'. In: 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Istanbul, Turkey 5 - 8 December 2023. [Conference or Workshop Item]

Stamate, Daniel; Haran, Riya; Rutkowska, Karolina; Davuloori, Pradyumna; Mercure, Evelyne; Addyman, Caspar and Tomlinson, Mark. 2023. 'Predicting High vs Low Mother-Baby Synchrony with GRU-Based Ensemble Models'. In: Artificial Neural Networks and Machine Learning – ICANN 2023. Heraklion, Crete, Greece 26-29 September 2023. [Conference or Workshop Item]

Musto, Henry; Stamate, Daniel; Pu, Ida and Stahl, Daniel. 2023. 'Predicting Alzheimer’s Disease Diagnosis Risk Over Time with Survival Machine Learning on the ADNI Cohort'. In: Computational Collective Intelligence. ICCCI 2023.. Budapest, Hungary 27–29 September 2023. [Conference or Workshop Item]

Akanuma, Asei; Stamate, Daniel and Bishop, Mark (J. M.). 2023. 'Predicting Colour Reflectance with Gradient Boosting and Deep Learning'. In: Artificial Intelligence Applications and Innovations. Leon, Spain 14 - 17 June 2023. [Conference or Workshop Item]

Akanuma, Asei and Stamate, Daniel. 2022. 'A Neural Network Approach to Estimating Color Reflectance with Product Independent Models'. In: 31st International Conference on Artificial Neural Network. Bristol, United Kingdom 6 - 9 September 2022. [Conference or Workshop Item]

Shamsutdinova, Diana; Stamate, Daniel; Roberts, Angus and Stahl, Daniel. 2022. 'Combining Cox Model and Tree-Based Algorithms to Boost Performance and Preserve Interpretability for Health Outcomes'. In: 18th IFIP International Conference on Artificial Intelligence Applications and Innovations. Hersonissos, Crete, Greece 17 - 20 June 2022. [Conference or Workshop Item]

Stamate, Daniel; Musto, Henry; Ajnakina, Olesya and Stahl, Daniel. 2022. 'Predicting Risk of Dementia with Survival Machine Learning and Statistical Methods: Results on the English Longitudinal Study of Ageing Cohort'. In: 18th IFIP International Conference on Artificial Intelligence Applications and Innovations - AIAI 2022. Hersonissos, Crete, Greece 17 - 20 June 2022. [Conference or Workshop Item]

Musto, Henry; Stamate, Daniel; Pu, Ida and Stahl, Daniel. 2022. 'A Machine Learning Approach for Predicting Deterioration in Alzheimer's Disease'. In: 20th IEEE International Conference on Machine Learning and Applications (ICMLA). Pasadena, CA, United States 13-16 December 2021. [Conference or Workshop Item]

Langham, John; Stamate, Daniel; Wu, Charlotte A.; Murtagh, Fionn; Morgan, Catharine; Reeves, David; Ashcroft, Darren; Kontopantelis, Evan and McMillan, Brian. 2022. 'Predicting risk of dementia with machine learning and survival models using routine primary care records'. In: 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Houston, TX, United States 9-12 December 2021. [Conference or Workshop Item]

Ermaliuc, Miha; Stamate, Daniel; Magoulas, George D. and Pu, Ida. 2021. 'Creating Ensembles of Generative Adversarial Network Discriminators for One-Class Classification'. In: International Conference on Engineering Applications of Neural Networks. Halkidiki, Greece 25–27 June 2021. [Conference or Workshop Item]

Olaniyan, Rapheal; Stamate, Daniel and Pu, Ida. 2021. 'A Two-Step Optimised BERT-Based NLP Algorithm for Extracting Sentiment from Financial News'. In: IFIP International Conference on Artificial Intelligence Applications and Innovations. Hersonissos, Crete, Greece 25–27 June 2021. [Conference or Workshop Item]

Logofătu, Doina; Sobol, Gil; Andersson, Christina; Stamate, Daniel; Balabanov, Kristiyan and Cejrowski, Tymoteusz. 2020. Particle swarm optimization algorithms for autonomous robots with deterministic leaders using space filling movements. Evolving Systems, 11(3), pp. 383-396. ISSN 1868-6478 [Article]

Stamate, Daniel; Smith, Richard; Tsygancov, Ruslan; Vorobev, Rostislav; Langham, John; Stahl, Daniel and Reeves, David. 2020. 'Applying Deep Learning to Predicting Dementia and Mild Cognitive Impairment'. In: Artificial Intelligence Applications and Innovations. Halkidiki, Greece. [Conference or Workshop Item]

Stamate, Daniel; Kim, Min; Proitsi, Petroula; Westwood, Sarah; Baird, Alison; Nevado-Holgado, Alejo; Hye, Abdul; Bos, Isabelle; Vos, Stephanie; Vandenberghe, Rik; Teunissen, Charlotte E; Kate, Mara Ten; Scheltens, Philip; Gabel, Silvy; Meersmans, Karen; Blin, Olivier; Richardson, Jill; Roeck, Ellen De; Engelborghs, Sebastiaan; Sleegeres, Kristel; Bordet, Régis; Rami, Lorena; Kettunen, Petronella; Tsolaki, Magd; Verhey, Frans; Alcolea, Daniel; Lléo, Alberto; Peyratout, Gwendoline; Tainta, Mikel; Johannsen, Peter; Freund-Levi, Yvonne; Frölich, Lutz; Dobricic, Valerija; Frisoni, Giovanni B; Molinuevo, José L; Wallin, Anders; Popp, Julius; Martinez-Lage, Pablo; Bertram, Lars; Blennow, Kaj; Zetterberg, Henrik; Streffer, Johannes; Visser, Pieter J; Lovestone, Simon and Legido-Quigley, Cristina. 2019. A metabolite-based machine learning approach to diagnose Alzheimer’s-type dementia in blood: Results from the European Medical Information Framework for Alzheimer's Disease biomarker discovery cohort. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 5, pp. 933-938. [Article]

Olaniyan, Rapheal; Stamate, Daniel; Pu, Ida; Zamyatin, Alexander; Vashkel, Anna and Marechal, Frederic. 2019. 'Predicting S&P 500 based on its constituents and their social media derived sentiment'. In: 11th International Conference on Computational Collective Intelligence ICCCI 2019. Hendaye, France 4-6 September 2019. [Conference or Workshop Item]

Stamate, Daniel; Katrinecz, Andrea; Stahl, Daniel; Verhagen, Simone J.W.; Delespaul, Philippe A.E.G.; van Os, Jim and Guloksuz, Sinan. 2019. Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches. Schizophrenia Research, 209, pp. 156-163. ISSN 0920-9964 [Article]

Nikolaev, Nikolay; Smirnov, Evgueni; Stamate, Daniel and Zimmer, Robert. 2019. A Regime-Switching Recurrent Neural Network Model Applied to Wind Time Series. Applied Soft Computing, 80, pp. 723-734. ISSN 1568-4946 [Article]

Stahl, Daniel and Stamate, Daniel. 2019. 'Data Science Challenges in Computational Psychiatry and Psychiatric Research'. In: 5th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2018). Turin, Italy 1-3 October 2018. [Conference or Workshop Item]

Stamate, Daniel; Alghambdi, Wajdi; Ogg, Jeremy; Hoile, Richard and Murtagh, Fionn. 2019. 'A Machine Learning Framework for Predicting Dementia and Mild Cognitive Impairment'. In: 17th IEEE International Conference on Machine Learning and Applications (ICMLA 2018). Orlando, Florida, United States 17-20 December 2018. [Conference or Workshop Item]

Marechal, Frederic; Stamate, Daniel; Olaniyan, Rapheal and Marek, Jiri. 2018. 'On XLE index constituents’ social media based sentiment informing the index trend and volatility prediction'. In: 10th International Conference on Computational Collective Intelligence (ICCCI 2018). Bristol, United Kingdom. [Conference or Workshop Item]

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; Logofatu, Doina and Zamyatin, Alexander. 2018. 'PIDT: A Novel Decision Tree Algorithm Based on Parameterised Impurities and Statistical Pruning Approaches'. In: 14th 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]

Belgrave, Danielle; Cassidy, Rachel; Stamate, Daniel; Custovic, Adnan; Fleming, Louise; Bush, Andrew and Saglani, Sejal. 2018. 'Predictive Modelling Strategies to Understand Heterogeneous Manifestations of Asthma in Early Life'. In: 16th IEEE International Conference on Machine Learning and Applications 2017. Cancun, Mexico. [Conference or Workshop Item]

Stamate, Daniel; Katrinecz, Andrea; Alghamdi, Wajdi; Stahl, Daniel; Delespaul, Philippe; van Os, Jim and Guloksuz, Sinan. 2017. 'Predicting Psychosis Using the Experience Sampling Method with Mobile Apps'. In: ICMLA 2017: 16th IEEE International Conference on Machine Learning and Applications (ICMLA). Cancun, Mexico 18-21 December 2017. [Conference or Workshop Item]

Logofătu, Doina; Sobol, Gil; Stamate, Daniel and Balabanov, Kristiyan. 2017. 'A Novel Space Filling Curves Based Approach to PSO Algorithms for Autonomous Agents'. In: ICCCI 2017: 9th International Conference on Computational Collective Intelligence. Nicosia, Cyprus. [Conference or Workshop Item]

Logofatu, Doina; Sobol, Gil and Stamate, Daniel. 2017. 'Particle Swarm Optimization Algorithms for Autonomous Robots with Leaders Using Hilbert Curves'. In: 18th International Conference on Engineering Applications of Neural Networks (EANN 2017). Athens, Greece. [Conference or Workshop Item]

Alghamdi, Wajdi; Stamate, Daniel; Vang, Katherine; Stahl, Daniel; Colizzi, Marco; Tripoli, Giada; Quattrone, Diego; Ajnakina, Olesya; Murray, Robin M. and Forti, Marta Di. 2016. 'A Prediction Modelling and Pattern Detection Approach for the First-Episode Psychosis Associated to Cannabis Use'. In: 15th IEEE International Conference on Machine Learning and Applications. Anaheim, California, United States. [Conference or Workshop Item]

Murtagh, Fionn; Olaniyan, Rapheal and Stamate, Daniel. 2015. 'A novel statistical and machine learning hybrid approach to predicting S&P500 using sentiment analysis'. In: 8th International Conference of the ERCIM Working Group on Computational and Methodological Statistics. Senate House, University of London, United Kingdom. [Conference or Workshop Item]

Olaniyan, Rapheal; Stamate, Daniel; Ouarbya, Lahcen and Logofatu, Doina. 2015. 'Sentiment and stock market volatility predictive modelling - A hybrid approach'. In: 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA). Paris, France. [Conference or Workshop Item]

Olaniyan, Rapheal; Stamate, Daniel and Logofatu, Doina. 2015. 'Social Web-based Anxiety Index's Predictive Information on S&P 500 Revisited'. In: SLDS 2015: 3rd International Syposium on Statistical Learning and Data Sciences. Royal Holloway UoL, Egham, United Kingdom. [Conference or Workshop Item]

Logofatu, Doina and Stamate, Daniel. 2014. 'Scalable Distributed Genetic Algorithm for Data Ordering Problem with Inversion Using MapReduce'. In: AIAI 2014: 10th IFIP International Conference on Artificial Intelligence Applications and Innovations. Rhodes, Greece. [Conference or Workshop Item]

Pu, Ida; Stamate, Daniel and Shen, Yuji. 2014. Improving time-efficiency in blocking expanding ring search for mobile ad hoc networks. Journal of Discrete Algorithms, 24, pp. 59-67. ISSN 1570-8667 [Article]

Stamate, Daniel and Pu, Ida. 2012. 'Imperfect Information Fusion Using Rules with Bilattice Based Fixpoint Semantics'. In: 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012. Catania, Italy. [Conference or Workshop Item]

Stamate, Daniel. 2010. 'Queries with Multivalued Logic-Based Semantics for Imperfect Information Fusion'. In: 40th IEEE International Symposium on Multiple-Valued Logic (ISMVL '10). Barcelona, Spain 26-28 May 2010. [Conference or Workshop Item]

Stamate, Daniel. 2008. 'Default Reasoning with Imperfect Information in Multivalued Logics'. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008). Dallas TX, United States 22-24 May 2008. [Conference or Workshop Item]

Stamate, Daniel. 2008. Imperfect Information Representation through Extended Logic Programs in Bilattices. In: Bernadette Bouchon-Meunier; Christophe Marsala; Maria Rifqi and Ronald R Yager, eds. UNCERTAINTY AND INTELLIGENT INFORMATION SYSTEMS. London: World Scientific, pp. 419-432. ISBN 978-981-279-234-1 [Book Section]

Stamate, Daniel and Qaiyumi, S.. 2007. 'Reduction in Dimensions and Clustering using Risk and Return Model'. In: IEEE International Symposium on Data Mining and Information Retrieval (IEEE DMIR-07) in conjunction with the IEEE 21 International Conference on Advanced Information Networking and Applications (IEEE AINA-07), Niagara Falls, Canada. UNDEFINED 5/1/2007. [Conference or Workshop Item]

Stamate, Daniel. 2006. 'Assumption based Multi-Valued Semantics for Extended Logic Programs'. In: 36th IEEE International Symposium on Multiple-Valued Logics (IEEE ISMVL 2006). UNDEFINED 5/1/2006. [Conference or Workshop Item]

Stamate, Daniel; Loyer, Y. and Spyratos, N.. 2004. Hypothesis-based semantics of logic programs in multivalued logics. ACM Transactions on Computational Logic, 5(3), pp. 508-527. ISSN 15293785 [Article]

Stamate, Daniel; Loyer, Y. and Spyratos, N.. 2003. Parametrized semantics of logic programs: a unifying framework. Theoretical Computer Science, 308(1-3), pp. 429-447. ISSN 03043975 [Article]