| Mining adverse drug events using multiple feature hierarchies and patient history windows M Bampa, P Papapetrou 2019 International Conference on Data Mining Workshops (ICDMW), 925-932, 2019 | 6 | 2019 |
| M-ClustEHR: A multimodal clustering approach for electronic health records M Bampa, I Miliou, B Jovanovic, P Papapetrou Artificial Intelligence in Medicine 154, 102905, 2024 | 5 | 2024 |
| Detecting adverse drug events from Swedish electronic health records using text mining M Bampa, H Dalianis Proceedings of the LREC 2020 Workshop on Multilingual Biomedical Text …, 2020 | 5 | 2020 |
| EpidRLearn: Learning Intervention Strategies for Epidemics with Reinforcement Learning M Bampa, T Fasth, S Magnusson, P Papapetrou International Conference on Artificial Intelligence in Medicine, 189-199, 2022 | 4 | 2022 |
| Machine learning models for automated interpretation of 12-lead electrocardiographic signals: a narrative review of techniques, challenges, achievements and clinical relevance P Pantelidis, M Bampa, E Oikonomou, P Papapetrou Journal of Medical Artificial Intelligence 6, 2023 | 3 | 2023 |
| Deep learning to diagnose left ventricular hypertrophy from standard, 12-lead ECG signals: a proof-of-concept study P Pantelidis, E Oikonomou, N Souvaliotis, M Spartalis, S Lampsas, ... Europace 25 (Supplement_1), euad122. 534, 2023 | 2 | 2023 |
| A clustering framework for patient phenotyping with application to adverse drug events M Bampa, P Papapetrou, J Hollmén 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems …, 2020 | 2 | 2020 |
| The Impact of Climate Change on the Mental Health of Populations at Disproportionate Risk of Health Impacts and Inequities: A Rapid Scoping Review of Reviews GA Alarcón Garavito, LF Toncón Chaparro, S Jasim, F Zanatta, I Miliou, ... International Journal of Environmental Research and Public Health 21 (11), 1415, 2024 | 1 | 2024 |
| Generative adversarial networks (GANs) to produce synthetic 12-lead electrocardiogram signals for specific and rare diseases: a novel, powerful tool towards clinical advancements P Pantelidis, E Oikonomou, M Bampa, I Gialamas, A Goliopoulou, ... European Heart Journal 45 (Supplement_1), ehae666. 3427, 2024 | | 2024 |
| Data-Driven AI for Patient and Public Health: On the Use of Multisource and Multimodal Data in Machine Learning to Improve Healthcare M Bampa Department of Computer and Systems Sciences, Stockholm University, 2024 | | 2024 |
| A Workflow for Creating Multimodal Machine Learning Models for Metastasis Predictions in Melanoma Patients F Rugolon, K Randl, M Bampa, P Papapetrou Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | | 2023 |
| Inside the “brain” of an artificial neural network: an interpretable deep learning approach to paroxysmal atrial fibrillation diagnosis from electrocardiogram signals during … P Pantelidis, E Oikonomou, S Lampsas, N Souvaliotis, M Spartalis, ... European Heart Journal-Digital Health 3 (4), ztac076. 2781, 2022 | | 2022 |
| A Workflow for Generating Patient Counterfactuals in Lung Transplant Recipients F Rugolon, M Bampa, P Papapetrou Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | | 2022 |
| Optimising and validating deep learning approaches for diagnosing atrial fibrillation from few-lead ambulatory electrocardiogram signals P Pantelidis, E Oikonomou, N Souvaliotis, M Spartalis, M Bampa, ... Europace 24 (Supplement_1), euac053. 561, 2022 | | 2022 |
| Aggregate-Eliminate-Predict: Detecting Adverse Drug Events from Heterogeneous Electronic Health Records M Bampa, P Papapetrou arXiv preprint arXiv:1907.06058, 2019 | | 2019 |
Panagiotis PapapetrouProfessor in Computer and Systems Sciences, Stockholm University, Swedendsv.su.se üzerinde doğrulanmış e-posta adresine sahip