D. Stamate

发表

A Machine Learning Framework for Predicting Dementia and Mild Cognitive Impairment

Fionn Murtagh, Jeremy Ogg, Daniel Stamate, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

Imperfect Information Representation through Extended Logic Programs in Bilattices

D. Stamate, 2008 .

A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort

K. Blennow, J. Molinuevo, P. Scheltens, 2019, Alzheimer's & dementia.

Update Rules and Revision Programs

D. Laurent, D. Stamate, N. Spyratos, 2007 .

New Mixed Ligand Co(II) Complexes as Possible Electrolytes for Dye-Sensitezed Solar Cells - A Combined Experimental and Computational Approach

D. Stamate, F. Cimpoesu, M. Gîrțu, 2014 .

Histopathological Study of Brain from Cattle with Nervous Symptomatology

D. Stamate, B. Georgescu, F. Bărbuceanu, 2015 .

Predicting risk of dementia with machine learning and survival models using routine primary care records

F. Murtagh, D. Stamate, E. Kontopantelis, 2021, 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

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 W

G. Magoulas, D. Stamate, I. Pu, 2022 .

From POPSICLE to CARoL in a Semester

D. Stamate, G. Trajkovski, Darush Davani, 2004 .

Applying Deep Learning to Predicting Dementia and Mild Cognitive Impairment

Daniel Stamate, David Reeves, Daniel Stahl, 2020, AIAI.

New insights in the bonding regime and ligand field in Wernerian complexes. A density functional study

D. Stamate, M. Ferbinteanu, F. Cimpoesu, 2013 .

A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort

Magda Tsolaki, Giovanni B. Frisoni, Min Kim, 2019, Alzheimer's & dementia.

Utilising symptom dimensions with diagnostic categories improves prediction of time to first remission in first-episode psychosis

R. Murray, C. Pariante, D. Stamate, 2017, Schizophrenia Research.

A New Machine Learning Framework for Understanding the Link Between Cannabis Use and First-Episode Psychosis

Robin M. Murray, Alexander Zamyatin, Daniel Stahl, 2018, eHealth.

Hypothesis-based semantics of logic programs in multivalued logics

Nicolas Spyratos, Daniel Stamate, Yann Loyer, 2004, TOCL.

Parametrized semantics of logic programs--a unifying framework

Nicolas Spyratos, Daniel Stamate, Yann Loyer, 2003, Theor. Comput. Sci..

Quantitative Semantics for Uncertain Knowledge Bases

Daniel Stamate, D. Stamate, 2012, IPMU.

Default Reasoning with Imperfect Information in Multivalued Logics

Daniel Stamate, D. Stamate, 2008, 38th International Symposium on Multiple Valued Logic (ismvl 2008).

Extended Deductive Databases with Uncertain Information

Daniel Stamate, D. Stamate, 2007 .

Assumption based multi-valued semantics for extended logic programs

Daniel Stamate, D. Stamate, 2006, 36th International Symposium on Multiple-Valued Logic (ISMVL'06).

Predictive Modelling Strategies to Understand Heterogeneous Manifestations of Asthma in Early Life

Rachel Cassidy, Daniel Stamate, Adnan Custovic, 2017, 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA).

Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches

Daniel Stahl, Daniel Stamate, Andrea Katrinecz, 2019, Schizophrenia Research.

A Prediction Modelling and Pattern Detection Approach for the First-Episode Psychosis Associated to Cannabis Use

Robin M. Murray, Daniel Stahl, Daniel Stamate, 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).

PIDT: A Novel Decision Tree Algorithm Based on Parameterised Impurities and Statistical Pruning Approaches

Doina Logofatu, Alexander Zamyatin, Daniel Stahl, 2018, AIAI.

DFT Study of Binding and Electron Transfer from a Metal-Free Dye with Carboxyl, Hydroxyl, and Sulfonic Anchors to a Titanium Dioxide Nanocluster

D. Stamate, F. Cimpoesu, M. Gîrțu, 2013 .

Creating Ensembles of Generative Adversarial Network Discriminators for One-Class Classification

Daniel Stamate, George D. Magoulas, Ida Pu, 2021, EANN.

Reduction in Dimensions and Clustering Using Risk and Return Model

Daniel Stamate, Sayed W. Qaiyumi, D. Stamate, 2007, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07).

A New Machine Learning Framework for Understanding the Link etween Cannabis Use and First-Episode Psychosis

D. Stamate, W. Alghamdi, D. Ståhl, 2018 .

A regime-switching recurrent neural network model applied to wind time series

Daniel Stamate, Evgueni Smirnov, Nikolay Y. Nikolaev, 2019, Appl. Soft Comput..

Predicting Psychosis Using the Experience Sampling Method with Mobile Apps

Daniel Stahl, Daniel Stamate, Wajdi Alghamdi, 2017, 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA).

Improving time-efficiency in blocking expanding ring search for mobile ad hoc networks

Daniel Stamate, Yuji Shen, Ida M. Pu, 2014, J. Discrete Algorithms.

A two-step optimised BERT-based natural language processing algorithm

D. Stamate, I. Pu, Rapheal Olaniyan, 2022 .

Technology of Informative Feature Selection for Immunosignature Analysis

S. A. Johnston, D. Stamate, A. A. Koshechkin, 2020, Sovremennye tekhnologii v meditsine.

Particle swarm optimization algorithms for autonomous robots with deterministic leaders using space filling movements

Tymoteusz Cejrowski, Daniel Stamate, Doina Logofătu, 2018, Evolving Systems.

Predicting Risk of Dementia with Survival Machine Learning and Statistical Methods: Results on the English Longitudinal Study of Ageing Cohort

D. Stamate, O. Ajnakina, H. Musto, 2023, AIAI Workshops.