Daniel Stamate - Publications

On a Survival Gradient Boosting, Neural Network and Cox PH based Approach to Predicting Dementia Diagnosis Risk on ADNI, 2023 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), 2023, accepted, to appear. Henry Musto, Daniel Stamate, Doina Logofatu, Lahcen Ouarbya

Joint Decision Making in Ant Colony Systems for Solving the Multiple Traveling Salesman Problem. Journal of Procedia Computer Science, Vol 225, Elsevier, December 2023, DOI https://doi.org/10.1016/j.procs.2023.10.345. Mihaela Breaban, Raluca Necula, Dorel Lucanu, Daniel Stamate

Predicting High vs Low Mother-Baby Synchrony with GRU-Based Ensemble Models. In: Iliadis, L., Papaleonidas, A., Angelov, P., Jayne, C. (eds) Artificial Neural Networks and Machine Learning – ICANN 2023. ICANN 2023. Lecture Notes in Computer Science, vol 14262. Springer, Cham. DOI https://doi.org/10.1007/978-3-031-44201-8_16. Daniel Stamate, Riya Haran, Karolina Rutkowska, Sree Davuloori, Evelyne Mercure, Caspar Addyman, Mark Tomlinson

Predicting Alzheimer’s Disease Diagnosis Risk Over Time with Survival Machine Learning on the ADNI Cohort. In: Nguyen, N.T., et al. Computational Collective Intelligence. ICCCI 2023. Lecture Notes in Computer Science(), vol 14162. Springer, Cham. https://doi.org/10.1007/978-3-031-41456-5_53 . Henry Musto, Daniel Stamate, Ida Pu, Daniel Stahl

Predicting Colour Reflectance with Gradient Boosting and Deep Learning. The19th IFIP International Conference on Artificial Intelligence Applications and Innovations - AIAI 2023, IFIP Advances in Information and Communication Technology, vol 675, Springer, DOI: https://doi.org/10.1007/978-3-031-34111-3_14.
Asei Akanuma, Daniel Stamate, Mark Bishop

A Neural Network Approach to Estimating Color Reflectance with Product Independent Models. The European Neural Network Society's 31st International Conference on Artificial Neural Networks, Springer, Lecture Notes in Computer Science, vol 13531, 2022, DOI: https://doi.org/10.1007/978-3-031-15934-3_66.
Asei Akanuma, Daniel Stamate

Predicting Risk of Dementia with Survival Machine Learning and Statistical Methods: Results on the English Longitudinal Study of Ageing Cohort. 18th IFIP International Conference on Artificial Intelligence Applications and Innovations - AIAI 2022, IFIP Advances in Information and Communication Technology, vol 652, Springer, 2022, DOI: https://doi.org/10.1007/978-3-031-08341-9_35
Daniel Stamate, Henry Musto, Olesya Ajnakina, Daniel Stahl

Combining Cox model and tree-based algorithms to boost performance and preserve interpretability for health outcomes. 18th IFIP International Conference on Artificial Intelligence Applications and Innovations - AIAI 2022, IFIP Advances in Information and Communication Technology, vol 652, Springer, 2022. DOI: https://doi.org/10.1007/978-3-031-08337-2_15
Diana Shamsutdinova, Daniel Stamate, Angus Roberts, Daniel Stahl

Predicting risk of dementia with machine learning and survival models using routine primary care records, In: Proceedings of 2021 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM2021), DOI: https://doi.org/10.1109/BIBM52615.2021.9669363. John Lanham, Daniel Stamate, Charlotte. A. Wu, Fionn Murtagh, Catharine Morgan, David Reeves, Darren Ashcroft, Evan Kontopantelis, Brian Mcmillan

A Machine Learning Approach for Predicting Deterioration in Alzheimer's Disease, In: Proceeding of 20th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), Publisher IEEE, December 2021, DOI: https://doi.org/10.1109/ICMLA52953.2021.00232. Henry Musto, Daniel Stamate, Ida Pu, Daniel Stahl

A two-step optimised BERT-based NLP algorithm for extracting sentiment from financial news, Proceedings of 17th Intl Conference of Artificial Intelligence Applications and Innovations, AIAI 2021, Springer, June 2021, DOI: https://doi.org/10.1007/978-3-030-79150-6_58. Rapheal Olaniyan, Daniel Stamate, Ida Pu

Creating Ensembles of Generative Adversarial Network Discriminators for One-class Classification, Proceedings of 22nd Intl Conference of Engineering Applications of Neural Networks, EANN 2021, Springer, June 2021, DOI: https://doi.org/10.1007/978-3-030-80568-5_2. Mihai Ermaliuc, Daniel Stamate, George Magoulas, Ida Pu

Particle swarm optimization algorithms for autonomous robots with deterministic leaders using space filling movements, Journal Evolving Systems, Springer, Volume 11, issue 3 (Special Issue: Evolving Intelligent Applications in Engineering), September 2020, pp 383–396, DOI: https://doi.org/10.1007/s12530-018-9245-9. Doina Logofătu, Gil Sobol, Christina Andersson, Daniel Stamate, Kristiyan Balabanov, Tymoteusz Cejrowski

Applying Deep Learning to Predicting Dementia and Mild Cognitive Impairment, Proc. of Intl. Conference of Artificial Intelligence Applications and Innovations. AIAI 2020. IFIP Advances in Information and Communication Technology, vol 584. Springer, Cham, DOI:https://doi.org/10.1007/978-3-030-49186-4_26. Daniel Stamate, Richard Smith, Ruslan Tsygancov, Rostislav Vorobev, John Langham, Daniel Stahl, David Reeves

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, Vol. 5, 2019, pp 933-938, Elsevier, 2019. 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. https://www.sciencedirect.com/science/article/pii/S2352873719300873

Predicting S&P 500 based on its constituents and their social media derived sentiment, Proc. 11th International Conference on Computational Collective Intelligence (ICCCI), 2019, Springer LNCS 11683, DOI: https://doi.org/10.1007/978-3-030-28377-3_12. Rapheal Olaniyan, Daniel Stamate, Ida Pu, Alexander Zamyatin, Anna Vashkel, Frederic Marechal

A Regime-Switching Recurrent Neural Network Model Applied to Wind Time Series, Applied Soft Computing (Journal, Elsevier), 2019, DOI: https://doi.org/10.1016/j.asoc.2019.04.009.
Nikolay Nikolaev, Evgueni Smirnov, Daniel Stamate, Robert Zimmer

Can dementia risk be predicted using routine electronic health records?
Society for Academic Primary Care Conference 2019 (SAPC ASM , Exeter), https://sapc.ac.uk/conference/2019/abstract/can-dementia-risk-be-predicted-using-routine-electronic-health-records_3e-1. Catharine Morgan, Darren M Ashcroft, Evan Kontopantelis, Daniel Stamate, David Reeves

Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches, J. Schizophrenia Research, Elsevier, 2019, DOI: https://doi.org/10.1016/j.schres.2019.04.028. Daniel Stamate, Andrea Katrinecz, Daniel Stah, ESM-MERGE Investigators, Simone J.W. Verhagen, Philippe A.E.G. Delespaul, Jim van Os, Sinan Guloksuz

A Machine Learning Framework for Predicting Dementia and Mild Cognitive Impairment, Proc. 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), 2018. DOI: 10.1109/ICMLA.2018.00107. Daniel Stamate, Wajdi Alghammdi, Jeremy Ogg, Richard Hoile, Fionn Murtagh

Data Science Challenges in Computational Psychiatry and Psychiatric Research. Proc. 5^th IEEE Data Science and Advanced Analytics, 2018. DOI: 10.1109/DSAA.2018.00067. Daniel Stahl, Daniel Stamate

On XLE index constituents’ social media based sentiment informing the index trend and volatility prediction. Proc. 10th International Conference on Computational Collective Intelligence (ICCCI), 2018, Springer LNCS. DOI https://doi.org/10.1007/978-3-319-98446-9_34. Frederic Marechal, Daniel Stamate, Rapheal Olaniyan, Jiri Marek

A New Machine Learning Framework for Understanding the Link between Cannabis Use and First-Episode Psychosis. Studies in Health Technology and Informatics 2018; 248:9-16, IOS Press, DOI 10.3233/978-1-61499-858-7-9. Wajdi Alghamdi, Daniel Stamate, Daniel Stahl, Alexander Zamyatin, Robin Murray, Marta di Forti

Predicting First-Episode Psychosis Associated with Cannabis Use with Artificial Neural Networks and Deep Learning. Proc. 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), 2018, Springer CCIS, DOI: https://doi.org/10.1007/978-3-319-91479-4_57. Daniel Stamate, Wajdi Alghamdi, Daniel Stahl, Ida Pu, Fionn Murtagh, Danielle Belgrave, Robin Murray and Marta di Forti

PIDT: A Novel Decision Tree Algorithm Based on Parameterised Impurities and Statistical Pruning Approaches, Proc. 14th International Conference on Artificial Intelligence Applications and Innovations (AIAI), 2018, Springer IFIP, DOI: https://doi.org/10.1007/978-3-319-92007-8_24. Daniel Stamate, Wajdi Alghamdi, Daniel Stahl, Doina Logofatu and Alexander Zamyatin

Can Artificial Neural Networks Predict Psychiatric Conditions Associated with Cannabis Use? Proc. 14th International Conference on Artificial Intelligence Applications and Innovations (AIAI), 2018, Springer IFIP, DOI: https://doi.org/10.1007/978-3-319-92007-8_27. Daniel Stamate, Wajdi Alghamdi, Daniel Stahl, Alexander Zamyatin, Robin Murray and Marta di Forti

Utilising symptom dimensions with diagnostic categories improves prediction of time to first remission in first-episode psychosis. Schizophrenia Research, DOI: https://doi.org/10.1016/j.schres.2017.07.042 , (Elsevier), 2018, pp. 391-398. Ajnakina, O., Lally, J., Di Forti, M., Stilo, S.A., Kolliakou, A., Gardner-Sood, P., Dazzan, P., Pariante, C., Marques, T.R., Mondelli, V., MacCabe, J., Gaughran, F., David, A.S., Stamate D., Murray, R.M., & Fisher, H.L

Predicting Psychosis Using the Experience Sampling Method with Mobile Applications.
Proceedings of 16th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), 2017, Publisher: IEEE, DOI: 10.1109/ICMLA.2017.00-84 Daniel Stamate, Andrea Katrinecz, Wajdi Alghamdi, Daniel Stahl, ESM-MERGE Group Investigators, Philippe Delespaul, Jim van Os, Sinan Guloksuz.

Predictive Modelling Strategies to Understand Heterogeneous Manifestations of Asthma in Early Life.
Proceedings of 16th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), 2017, Publisher: IEEE, DOI 10.1109/ICMLA.2017.0-176. Daniel Stamate, Danielle Belgrave, Rachel Cassidy, Adnan Custovic, Louise Fleming, Andrew Bush and Sejal Saglani.

Particle Swarm Optimization Algorithms for Autonomous Robots with Leaders Using Hilbert Curves.
Proceedings of 18th International Conference on Engineering Applications of Neural Networks (EANN), 2017, Publisher: Springer, DOI: https://doi.org/10.1007/978-3-319-65172-9_45. Doina Logofatu, Gil Sobol, Daniel Stamate

A Novel Space Filling Curves Based Approach to PSO Algorithms for Autonomous Agents.
Proceedings of 9th International Conference on Computational Collective Intelligence (ICCCI), 2017, Publisher: Springer, DOI: https://doi.org/10.1007/978-3-319-67074-4_35. Doina Logofatu, Gil Sobol, Daniel Stamate, Kristiyan Balabanov

A Prediction Modelling and Pattern Detection Approach for the First-Episode Psychosis Associated to Cannabis Use. Proceedings of 15th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), 2016, Publisher: IEEE, DOI: 10.1109/ICMLA.2016.0148. Wajdi Alghamdi, Daniel Stamate, Katherine Vang, Daniel Stahl, Marco Colizzi, Giada Tripoli, Diego Quattrone, Olesya Ajnakina, Robin M. Murray and Marta Di Forti

Sentiment and Stock Market Volatility Predictive Modelling - a Hybrid Approach.
Proceedings of the 2nd IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA), 2015, Publisher: IEEE, DOI: 10.1109/DSAA.2015.7344855. Rapheal Olaniyan, Daniel Stamate, Doina Logofatu, Lahcen Ouarbya

A Novel Statistical and Machine Learning Hybrid Approach to Predicting S&P 500 using Sentiment Analysis.  Proceedings of the 8^th International Conference of the ERCIM Working Group on Computational and Methodological Statistics, and International Conference on Computational and Financial Econometrics, 2015. Fionn Murtagh, Rapheal Olaniyan, Daniel Stamate

Social Web-Based Anxiety Index’s Predictive Information on S&P 500, Revisited.
Proceedings of the 3rd International Symposium on Statistical Learning and Data Sciences (SLDS), 2015, Springer LNAI. DOI https://doi.org/10.1007/978-3-319-17091-6_15. Rapheal Olaniyan, Daniel Stamate, Doina Logofatu

Improving Time-Efficiency in Blocking Expanding Ring Search for Mobile Ad Hoc Networks.
Journal of Discrete Algorithms, Volume 24, 2014, pp. 59-67. DOI: https://doi.org/10.1016/j.jda.2013.03.006 Ida Pu, Daniel Stamate and Yuji Shen

Scalable Distributed Genetic Algorithm for Data Ordering Problem with Inversion Using MapReduce.
Proceedings of the 10th International Conference on Artificial Intelligence Applications and Innovations (AIAI), 2014, Springer 2014 IFIP Advances in Information and Communication Technology. DOI https://doi.org/10.1007/978-3-662-44654-6_32, Doina Logofatu, Daniel Stamate

Quantitative Semantics for Uncertain Knowledge Bases. Proceedings of the 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), 2012, Springer LNAI/CCIS. Daniel Stamate

Imperfect Information Fusion using Rules with Bilattice based Fixpoint Semantics.
Proc. of the 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), 2012, Springer LNAI/CCIS. Daniel Stamate, Ida Pu

Fixpoint Semantics for Extended Logic Programs on Bilattice based Multivalued Logics, and Applications. Proceedings of ManyVal Conference, 2012. Daniel Stamate, Ida Pu

Queries with Multivalued Logic based Semantics for Imperfect Information Fusion.
Proceedings of the 40th IEEE International Symposium on Multiple-Valued Logics (IEEE ISMVL), 2010. Daniel Stamate

A Bilattice based Fixed Point Semantics for Integrating Imperfect Information. Proceedings of the 6th Workshop on Fixed Points in Computer Science (FICS), 2009. Daniel Stamate

Default Reasoning with Imperfect Information in Multivalued Logics. Proceedings of the 38th IEEE International Symposium on Multiple-Valued Logics (IEEE ISMVL), 2008. Daniel Stamate

Imperfect Information Representation through Extended Logic Programs in Bilattices.
Uncertainty and Intelligent Information Systems, B.Bouchon-Meunier, R.R. Yager, C. Marsala, and M. Rifqi (Eds.), World Scientific, ISBN 978-981-279-234-1, 2008. Daniel Stamate

Reduction in Dimensions and Clustering using Risk and Return Model.
Proceedings of the IEEE International Symposium on Data Mining and Information Retrieval (IEEE DMIR), 2007. S.W. Qaiyumi, D. Stamate

Representing Imperfect Information through Extended Logic Programs in Multivalued Logics. Proceedings of the 11th biennial Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), 2006. Daniel Stamate

Assumption based Multiple-Valued Semantics for Extended Logic Programs. Proceedings of the 36th IEEE International Symposium on Multiple-Valued Logics (IEEE ISMVL), 2006. Daniel Stamate

Hypothesis-based Semantics of Logic Programs in Multivalued Logics. ACM Transactions on Computational Logic 15(3), 2004, pp. 508-527. Yann Loyer, Nicolas Spyratos, Daniel Stamate

Parameterized Semantics for Logic Programs - a Unifying Framework. Theoretical Computer Science 308(1-3), Elsevier, 2003, pp. 429-447. Yann Loyer, Nicolas Spyratos, Daniel Stamate

Hypothesis Support for Information Integration in Four-Valued Logics.  Proceedings of IFIP International Conference on Theoretical Computer Science, LNCS No. 1872, Springer, pp. 536-548, 2000. Yann Loyer, Nicilas Spyratos, Daniel Stamate

Integration of Information in Four-Valued Logics under Non-Uniform Assumptions. Proceedings of the 30th IEEE International Symposium on Multiple-Valued Logics (ISMVL), 2000, pp. 185-191. Yann Loyer, Niclas Spyratos, Daniel Stamate

Test d'Hypothèses pour l'Intégration d'Informations en Logique à Quatre Valeurs. Proceedings of JFPLC'2000 (Journées Francophones de Programmation Logique et Programmation
par Contraintes), Hermes, 2000, pp. 265-278. Y. Loyer, N. Spyratos, D. Stamate

Hypotheses Based Semantics for Information Integration in Four-valued Logics. Proceedings of the Fixed Points in Computer Science Workshop (FICS), 2000. Yann Loyer, Nicilas Spyratos, Daniel Stamate

Interfacing Decision Support Systems under Incomplete Information. Proceedings of the 25th International Conference on Information and Communication Technologies  and Programming, 2000, pp. 21-31. Yann Loyer,  Nicolas Spyratos, Daniel Stamate

Interfacing Decision Support Systems under Incomplete Information. International Journal Information Theories and Applications 7(1), 2000, pp. 38-48. Yann Loyer, Nicolas Spyratos, Daniel Stamate

Computing and Comparing Semantics of Programs in Four-valued Logics. Proceedings of the 24th International Symposium on Mathematical  Foundations of Computer Science (MFCS), 1999,
LNCS No. 1672, Springer, pp. 59-69. Yann Loyer, Nicolas Spyratos, Daniel Stamate

Deterministic Enforcement of Constraints. Journal of Programming and Computer Software 24, 1998, pp. 71-83. Dominique Laurent, Nicolas Spyratos, Daniel Stamate

Unification des Semantiques Usuelles de Programmes Logiques. Proceedings of JFPLC'98 (Journées Francophones de Programmation Logique et Programmation par Contraintes), Hermes, 1998, pp. 135-150. Y. Loyer, N. Spyratos, D. Stamate

Semantics and Containment of Queries with Internal and External conjunctions.  Proceedings of the 6th International Conference on Database Theory (ICDT), 1997, LNCS  No. 1186  Springer, pp. 71-82. Gosta Grahne,  Nicolas Spyratos, Daniel Stamate

Semantics and Containment of Queries in Multimedia Information Systems. Proceedings of the 2nd International Workshop on Multimedia Information Systems, 1997, pp. 82-87. Gosta Grahne, Nicolas Spyratos, Daniel Stamate

Multivalued Stable Semantics for Updating Databases with Uncertain Information. Frontiers in Artificial Intelligence and Applications: Information Modelling and Knowledge Bases VIII, H. Kangassalo et al. (eds), IOS Press, pp. 129-144, ISBN 905199334X, 1997. Nicolas Spyratos, Daniel Stamate

Bases de Données avec Informations Incertaines. Sémantique et Mises à Jour. Proceedings of JFPLC'96 (Journées Francophones de Programmation Logique et Programmation
par Contraintes), Hermes, 1996,  pp. 49-63. N. Spyratos, D. Stamate

A Class of Active Database Constraints. Proceedings of the International Conference on Information Technology, 1996.  M. Halfeld Ferrari Alves, D. Laurent, N. Spyratos, D. Stamate

Answer-Perturbation Techniques for the Protection of Statistical Databases. Statistics and Computing 5, Springer, 1995, pp. 203-213. Daniel Stamate, Henri Luchian

A general Model for the Answer-Perturbation Techniques. Proceedings of the 7th International Working Conference on Scientific and Statistical Database Management (SSDBM), 1994, Charlottesville, USA,  pp. 90-96. Daniel Stamate, Henri Luchian, Ben Paechter

Statistical Protection for Statistical Databases. Proceedings of the 6th International Working Conference on Scientific and Statistical Database Management (SSDBM), 1992, Ascona, Switzerland, pp. 160-177. Henri Luchian, Daniel Stamate

User-Oriented Approach for the Protection of Statistical Databases. Scientific Annals of "Alexandru Ioan Cuza" University of Iasi, vol. 1, Computer Science, 1992, pp. 41-55. Henri Luchian and Daniel Stamate