Items Authored/Edited by Stamate, Daniel
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Number of items: 43.
Article
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; 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]
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]
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]
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]
Book Section
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]
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]
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]
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]
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]