| Generalized random shapelet forests I Karlsson, P Papapetrou, H Boström Data mining and knowledge discovery 30, 1053-1085, 2016 | 183 | 2016 |
| Seq2Seq RNNs and ARIMA models for Cryptocurrency Prediction: A Comparative Study J Rebane, I Karlsson, S Denic, P Papapetrou Proc. of the ACM KDD, 2018 | 91 | 2018 |
| A classification framework for exploiting sparse multi-variate temporal features with application to adverse drug event detection in medical records F Bagattini, I Karlsson, J Rebane, P Papapetrou BMC medical informatics and decision making 19, 1-20, 2019 | 43 | 2019 |
| Explainable time series tweaking via irreversible and reversible temporal transformations I Karlsson, J Rebane, P Papapetrou, A Gionis 2018 IEEE International Conference on Data Mining (ICDM), 207-216, 2018 | 43 | 2018 |
| Predicting adverse drug events by analyzing electronic patient records I Karlsson, J Zhao, L Asker, H Boström Artificial Intelligence in Medicine: 14th Conference on Artificial …, 2013 | 36 | 2013 |
| Prediction of environmental controversies and development of a corporate environmental performance rating methodology J Svanberg, T Ardeshiri, I Samsten, P Öhman, T Rana, M Danielson Journal of Cleaner Production 344, 130979, 2022 | 28 | 2022 |
| Locally and globally explainable time series tweaking I Karlsson, J Rebane, P Papapetrou, A Gionis Knowledge and Information Systems 62 (5), 1671-1700, 2020 | 26 | 2020 |
| Exploiting complex medical data with interpretable deep learning for adverse drug event prediction J Rebane, I Samsten, P Papapetrou Artificial Intelligence in Medicine 109, 101942, 2020 | 22 | 2020 |
| Handling sparsity with random forests when predicting adverse drug events from electronic health records I Karlsson, H Boström 2014 ieee international conference on healthcare informatics, 17-22, 2014 | 21 | 2014 |
| Corporate governance performance ratings with machine learning J Svanberg, T Ardeshiri, I Samsten, P Öhman, PE Neidermeyer, T Rana, ... Intelligent Systems in Accounting, Finance and Management 29 (1), 50-68, 2022 | 19 | 2022 |
| Counterfactual explanations for survival prediction of cardiovascular ICU patients Z Wang, I Samsten, P Papapetrou Artificial Intelligence in Medicine: 19th International Conference on …, 2021 | 19 | 2021 |
| Forests of randomized shapelet trees I Karlsson, P Papapetrou, H Boström Statistical Learning and Data Sciences: Third International Symposium, SLDS …, 2015 | 18 | 2015 |
| Goldeneye++: A closer look into the black box A Henelius, K Puolamäki, I Karlsson, J Zhao, L Asker, H Boström, ... Statistical Learning and Data Sciences: Third International Symposium, SLDS …, 2015 | 16 | 2015 |
| Learning time series counterfactuals via latent space representations Z Wang, I Samsten, R Mochaourab, P Papapetrou Discovery Science: 24th International Conference, DS 2021, Halifax, NS …, 2021 | 14 | 2021 |
| An investigation of interpretable deep learning for adverse drug event prediction J Rebane, I Karlsson, P Papapetrou 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems …, 2019 | 14 | 2019 |
| Conformal prediction using random survival forests H Bostrom, L Asker, R Gurung, I Karlsson, T Lindgren, P Papapetrou 2017 16th IEEE International Conference on Machine Learning and Applications …, 2017 | 14* | 2017 |
| Predicting adverse drug events using heterogeneous event sequences I Karlsson, H Boström 2016 IEEE International Conference on Healthcare Informatics (ICHI), 356-362, 2016 | 14 | 2016 |
| Post hoc explainability for time series classification: Toward a signal processing perspective R Mochaourab, A Venkitaraman, I Samsten, P Papapetrou, CR Rojas IEEE signal processing magazine 39 (4), 119-129, 2022 | 13 | 2022 |
| Surveillance of communicable diseases using social media: A systematic review P Pilipiec, I Samsten, A Bota PLoS One 18 (2), e0282101, 2023 | 10 | 2023 |
| SMILE: a feature-based temporal abstraction framework for event-interval sequence classification J Rebane, I Karlsson, L Bornemann, P Papapetrou Data mining and knowledge discovery 35 (1), 372-399, 2021 | 10 | 2021 |
Panagiotis PapapetrouProfessor, Stockholm University, Sweden在 dsv.su.se 的电子邮件经过验证
