Browse by Goldsmiths authors: Stamate, Daniel
Number of items: 47.
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. (2024)
Reeves, David; Morgan, Catharine; Stamate, Daniel; Ford, Elizabeth; Ashcroft, Darren M.; Kontopantelis, Evangelos; Van Marwijk, Harm and McMillan, Brian
Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling. (2024)
Musto, Henry; Stamate, Daniel; Logofatu, Doina and Stahl, Daniel
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Ensembles of Bidirectional LSTM and GRU Neural Nets for Predicting Mother-Infant Synchrony in Videos. (2024)
Stamate, Daniel; Davuloori, Pradyumna; Logofatu, Doina; Mercure, Evelyne; Addyman, Caspar and Tomlinson, Mark
On a Survival Gradient Boosting, Neural Network and Cox PH Based Approach to Predicting Dementia Diagnosis Risk on ADNI. (2024)
Musto, Henry; Stamate, Daniel; Logofatu, Doina and Ouarbya, Lahcen
2023
Predicting High vs Low Mother-Baby Synchrony with GRU-Based Ensemble Models. (2023)
Stamate, Daniel; Haran, Riya; Rutkowska, Karolina; Davuloori, Pradyumna; Mercure, Evelyne; Addyman, Caspar and Tomlinson, Mark
Predicting Alzheimer’s Disease Diagnosis Risk Over Time with Survival Machine Learning on the ADNI Cohort. (2023)
Musto, Henry; Stamate, Daniel; Pu, Ida and Stahl, Daniel
Predicting Colour Reflectance with Gradient Boosting and Deep Learning. (2023)
Akanuma, Asei; Stamate, Daniel and Bishop, Mark (J. M.)
2022
A Neural Network Approach to Estimating Color Reflectance with Product Independent Models. (2022)
Akanuma, Asei and Stamate, Daniel
Combining Cox Model and Tree-Based Algorithms to Boost Performance and Preserve Interpretability for Health Outcomes. (2022)
Shamsutdinova, Diana; Stamate, Daniel; Roberts, Angus and Stahl, Daniel
Predicting Risk of Dementia with Survival Machine Learning and Statistical Methods: Results on the English Longitudinal Study of Ageing Cohort. (2022)
Stamate, Daniel; Musto, Henry; Ajnakina, Olesya and Stahl, Daniel
A Machine Learning Approach for Predicting Deterioration in Alzheimer's Disease. (2022)
Musto, Henry; Stamate, Daniel; Pu, Ida and Stahl, Daniel
Predicting risk of dementia with machine learning and survival models using routine primary care records. (2022)
Langham, John; Stamate, Daniel; Wu, Charlotte A.; Murtagh, Fionn; Morgan, Catharine; Reeves, David; Ashcroft, Darren; Kontopantelis, Evan and McMillan, Brian
2020
Particle swarm optimization algorithms for autonomous robots with deterministic leaders using space filling movements. (2020)
Logofătu, Doina; Sobol, Gil; Andersson, Christina; Stamate, Daniel; Balabanov, Kristiyan and Cejrowski, Tymoteusz
Applying Deep Learning to Predicting Dementia and Mild Cognitive Impairment. (2020)
Stamate, Daniel; Smith, Richard; Tsygancov, Ruslan; Vorobev, Rostislav; Langham, John; Stahl, Daniel and Reeves, David
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. (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
Predicting S&P 500 based on its constituents and their social media derived sentiment. (2019)
Olaniyan, Rapheal; Stamate, Daniel; Pu, Ida; Zamyatin, Alexander; Vashkel, Anna and Marechal, Frederic
Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches. (2019)
Stamate, Daniel; Katrinecz, Andrea; Stahl, Daniel; Verhagen, Simone J.W.; Delespaul, Philippe A.E.G.; van Os, Jim and Guloksuz, Sinan
A Regime-Switching Recurrent Neural Network Model Applied to Wind Time Series. (2019)
Nikolaev, Nikolay; Smirnov, Evgueni; Stamate, Daniel and Zimmer, Robert
Data Science Challenges in Computational Psychiatry and Psychiatric Research. (2019)
Stahl, Daniel and Stamate, Daniel
A Machine Learning Framework for Predicting Dementia and Mild Cognitive Impairment. (2019)
Stamate, Daniel; Alghambdi, Wajdi; Ogg, Jeremy; Hoile, Richard and Murtagh, Fionn
2018
On XLE index constituents’ social media based sentiment
informing the index trend and volatility prediction. (2018)
Marechal, Frederic; Stamate, Daniel; Olaniyan, Rapheal and Marek, Jiri
Can Artificial Neural Networks Predict Psychiatric Conditions Associated with Cannabis Use? (2018)
Stamate, Daniel; Alghamdi, Wajdi; Stahl, Daniel; Zamyatin, Alexander; Murray, Robin and di Forti, Marta
PIDT: A Novel Decision Tree Algorithm Based on Parameterised Impurities and Statistical Pruning Approaches. (2018)
Stamate, Daniel; Alghamdi, Wajdi; Stahl, Daniel; Logofatu, Doina and Zamyatin, Alexander
Predicting First-Episode Psychosis Associated with Cannabis Use with Artificial Neural Networks and Deep Learning. (2018)
Stamate, Daniel; Alghamdi, Wajdi; Stahl, Daniel; Pu, Ida; Murtagh, Fionn; Belgrave, Danielle; Murray, Robin and di Forti, Marta
A New Machine Learning Framework for Understanding the Link between Cannabis Use and First-Episode Psychosis. (2018)
Walghamdi, Wajdi; Stamate, Daniel; Stahl, Daniel; Murray, Robin and Di Forti, Marta
Utilising symptom dimensions with diagnostic categories improves prediction of time to first remission in first-episode psychosis. (2018)
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.
Predictive Modelling Strategies to Understand Heterogeneous Manifestations of Asthma in Early Life. (2018)
Belgrave, Danielle; Cassidy, Rachel; Stamate, Daniel; Custovic, Adnan; Fleming, Louise; Bush, Andrew and Saglani, Sejal
2017
Predicting Psychosis Using the Experience Sampling Method with Mobile Apps. (2017)
Stamate, Daniel; Katrinecz, Andrea; Alghamdi, Wajdi; Stahl, Daniel; Delespaul, Philippe; van Os, Jim and Guloksuz, Sinan
A Novel Space Filling Curves Based Approach to PSO Algorithms for Autonomous Agents. (2017)
Logofătu, Doina; Sobol, Gil; Stamate, Daniel and Balabanov, Kristiyan
Particle Swarm Optimization Algorithms for Autonomous Robots with Leaders Using Hilbert Curves. (2017)
Logofatu, Doina; Sobol, Gil and Stamate, Daniel
2016
A Prediction Modelling and Pattern Detection Approach for the First-Episode Psychosis Associated to Cannabis Use. (2016)
Alghamdi, Wajdi; Stamate, Daniel; Vang, Katherine; Stahl, Daniel; Colizzi, Marco; Tripoli, Giada; Quattrone, Diego; Ajnakina, Olesya; Murray, Robin M. and Forti, Marta Di
2015
A novel statistical and machine learning hybrid approach to predicting S&P500 using sentiment analysis. (2015)
Murtagh, Fionn; Olaniyan, Rapheal and Stamate, Daniel
Sentiment and stock market volatility predictive modelling - A hybrid approach. (2015)
Olaniyan, Rapheal; Stamate, Daniel; Ouarbya, Lahcen and Logofatu, Doina
Social Web-based Anxiety Index's Predictive
Information on S&P 500 Revisited. (2015)
Olaniyan, Rapheal; Stamate, Daniel and Logofatu, Doina
