Oscillator synthesis based on Nambu mechanics with canonical dissipative damping. - Wolfgang Mathis; Daniel Stahl; Richard Mathis (ECCTD, 2013)

The Impact of Agile Principles and Practices on Large-Scale Software Development Projects: A Multiple-Case Study of Two Projects at Ericsson. - Lina Lagerberg; Tor Skude; Pär Emanuelsson; Kristian Sandahl; Daniel Stahl (ESEM, 2013)

A Prediction Modelling and Pattern Detection Approach for the First-Episode Psychosis Associated to Cannabis Use. - Wajdi Alghamdi; Daniel Stamate; Katherine Vang; Daniel Stahl; Marco Colizzi; Giada Tripoli; Diego Quattrone; Olesya Ajnakina; Robin M. Murray; Marta Di Forti (ICMLA, 2016)

Predicting Psychosis Using the Experience Sampling Method with Mobile Apps. - Daniel Stamate; Andrea Katrinecz; Wajdi Alghamdi; Daniel Stahl; Philippe Delespaul; Jim van Os; Sinan Guloksuz (ICMLA, 2017)

Data Science Challenges in Computational Psychiatry and Psychiatric Research. - Daniel Stahl; Daniel Stamate (DSAA, 2018)

A New Machine Learning Framework for Understanding the Link Between Cannabis Use and First-Episode Psychosis. - Wajdi Alghamdi; Daniel Stamate; Daniel Stahl; Alexander Zamyatin; Robin M. Murray; Marta Di Forti (eHealth, 2018)

PIDT: A Novel Decision Tree Algorithm Based on Parameterised Impurities and Statistical Pruning Approaches. - Daniel Stamate; Wajdi Alghamdi; Daniel Stahl; Doina Logofatu; Alexander Zamyatin (AIAI, 2018)

Can Artificial Neural Networks Predict Psychiatric Conditions Associated with Cannabis Use? - Daniel Stamate; Wajdi Alghamdi; Daniel Stahl; Alexander Zamyatin; Robin M. Murray; Marta Di Forti (AIAI, 2018)

Predicting First-Episode Psychosis Associated with Cannabis Use with Artificial Neural Networks and Deep Learning. - Daniel Stamate; Wajdi Alghamdi; Daniel Stahl; Ida M. Pu; Fionn Murtagh; Danielle Belgrave; Robin M. Murray; Marta Di Forti (IPMU (3), 2018)

Using Virtual Reality to Assess Associations Between Paranoid Ideation and Components of Social Performance: A Pilot Validation Study. - Simon Riches; Philippa Garety; Mar Rus-Calafell; Daniel Stahl; Clare Evans; Nikolaos Sarras; Keren Yeboah; Lucia Valmaggia (Cyberpsychology Behav. Soc. Netw., 2019)

Functional connectivity changes associated with fMRI neurofeedback of right inferior frontal cortex in adolescents with ADHD. - Katya Rubia; Marion Criaud; M. Wulff; A. Alegria; H. Brinson; Gareth J. Barker; Daniel Stahl; Vincent Giampietro (NeuroImage, 2019)

Applying Deep Learning to Predicting Dementia and Mild Cognitive Impairment. - Daniel Stamate; Richard Smith; Ruslan Tsygancov; Rostislav Vorobev; John Langham; Daniel Stahl; David Reeves (AIAI (2), 2020)

A Machine Learning Approach for Predicting Deterioration in Alzheimer's Disease. - Henry Musto; Daniel Stamate; Ida M. Pu; Daniel Stahl (ICMLA, 2021)

Remote Smartphone-Based Speech Collection: Acceptance and Barriers in Individuals with Major Depressive Disorder. - Judith Dineley; Grace Lavelle; Daniel Leightley; Faith Matcham; Sara Siddi; Maria Teresa Peñarrubia-María; Katie M. White; Alina Ivan; Carolin Oetzmann; Sara Simblett; Erin Dawe-Lane; Stuart Bruce; et al. (Interspeech, 2021)

Remote smartphone-based speech collection: acceptance and barriers in individuals with major depressive disorder. - Judith Dineley; Grace Lavelle; Daniel Leightley; Faith Matcham; Sara Siddi; Maria Teresa Peñarrubia-María; Katie M. White; Alina Ivan; Carolin Oetzmann; Sara Simblett; Erin Dawe-Lane; Stuart Bruce; et al. (CoRR, 2021)

Combining Cox Model and Tree-Based Algorithms to Boost Performance and Preserve Interpretability for Health Outcomes. - Diana Shamsutdinova; Daniel Stamate; Angus Roberts; Daniel Stahl (AIAI (2), 2022)

Predicting Risk of Dementia with Survival Machine Learning and Statistical Methods: Results on the English Longitudinal Study of Ageing Cohort. - Daniel Stamate; Henry Musto; Olesya Ajnakina; Daniel Stahl (AIAI (Workshops), 2022)

Predicting Alzheimer's Disease Diagnosis Risk Over Time with Survival Machine Learning on the ADNI Cohort. - Henry Musto; Daniel Stamate; Ida M. Pu; Daniel Stahl (ICCCI, 2023)

Predicting Alzheimers Disease Diagnosis Risk over Time with Survival Machine Learning on the ADNI Cohort. - Henry Musto; Daniel Stamate; Ida M. Pu; Daniel Stahl (CoRR, 2023)

Sample Size in Natural Language Processing within Healthcare Research. - Jaya Chaturvedi; Diana Shamsutdinova; Felix Zimmer; Sumithra Velupillai; Daniel Stahl; Robert Stewart 002; Angus Roberts (CoRR, 2023)

Predicting type 2 diabetes prevalence for people with severe mental illness in a multi-ethnic East London population. - Diana Shamsutdinova; Jayati Das-Munshi; Mark Ashworth; Angus Roberts; Daniel Stahl (Int. J. Medical Informatics, 2023)

Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling. - Henry Musto; Daniel Stamate; Doina Logofatu; Daniel Stahl (ICANN (8), 2024)

Variational Encoder Based Synthetic Alzheimer's Data Generation for Deep Learning, XGBoost and Statistical Survival Analysis. - Henry Musto; Daniel Stamate; Daniel Stahl (ICMLA, 2024)

Classifying Cognitive States of Alzheimer's Disease with Machine Learning Using Digital Biomarkers from the Bio-Hermes Study Cohort. - Eoin Houstoun; Daniel Stamate; Henry Musto; David Reeves; Catharine Morgan; Roxana Hutanu; Kalliopi Mavromati; Dorina Cadar; Daniel Stahl (AIAI (4), 2025)

Proteomics, Neuropsychological and Demographics Multimodal Machine Learning Approach to Alzheimer's Disease Prediction on the Bio-Hermes Study Cohort. - Henry Musto; Daniel Stamate; David Reeves; Catharine Morgan; Roxana Hutanu; Kalliopi Mavromati; Dorina Cadar; Daniel Stahl (AIAI (4), 2025)

Balancing accuracy and Interpretability: An R package assessing complex relationships beyond the Cox model and applications to clinical prediction. - Diana Shamsutdinova; Daniel Stamate; Daniel Stahl (Int. J. Medical Informatics, 2025)

EHR-based prediction modelling meets multimodal deep learning: A systematic review of structured and textual data fusion methods. - Ariel Soares Teles; Ivan Rodrigues de Moura; Francisco Silva; Angus Roberts; Daniel Stahl (Inf. Fusion, 2025)