Contact

• Mail: isak-kar@dsv.su.se
• Room: 7408
• Tel.: 08-16 16 76 or 073-270 10 66

Publications

• Francesco Bagattini, Isak Karlsson, Jonathan Rebane, Panagiotis Papapetrou, A classification framework for exploiting sparse multi-variate temporal features with application to adverse drug event detection in medical records. In BMC Medical Informatics and Decision Making 19 (1), 7, 2019
• Jonathan Rebane, Isak Karlsson, and Panagiotis Papapetrou, An Investigation of Interpretable Deep Learning for Adverse Drug Event Prediction. In the IEEE International Symposium on Computer-Based Medical Systems (CBMS) 2019
• Isak Karlsson, Jonathan Rebane, Panagiotis Papapetrou, and Aristides Gionis, Locally and globally explainable time series tweaking. In Knowledge and Information Systems (KAIS), 2019
• Lindgren, Panagiotis Papapetrou, Lars Asker and Isak Samsten, Example-based feature tweaking using random forests. In the IEEE International Conference on Information Reuse and Integration for Data Science (IRI) 2019.
• Isak Karlsson, Jonathan Rebane, Panagiotis Papapetrou, and Aristides Gionis, Explainable time series tweaking via irreversible and reversible temporal transformations. In the IEEE International Conference on Data Mining (ICDM), 2018
• Jonathan Rebane, Isak Karlsson, Panagiotis Papapetrou, and Jonathan Rebane, Seq2Seq RNNs and ARIMA models for Cryptocurrency Prediction: A Comparative Study. In Proceedings of the FinTech Workshop at the International Conference of Knowledge Discovery and Data Mining (KDD FinTech Workshop), 2018
• Jaakko Hollmén, Lars Asker, Isak Karlsson, Panagiotis Papapetrou, Henrik Boström, Birgitta Norstedt Wikner, Inger Öhman, Exploring epistaxis as an adverse effect of anti-thrombotic drugs and outdoor temperature. In Proceedings of the International Conference on Pervasive Technologies Related to Assistive Environments (PETRA) 2018: 1-4
• Henrik Boström, Lars Asker, Ram Gurung, Isak Karlsson, Tony Lindgren, and Panagiotis Papapetrou, Conformal prediction using random survival forests. In Proceedings of International Conference On Machine Learning And Applications (ICMLA), 2017
• Isak Karlsson, Panagiotis Papapetrou, and Lars Asker, KAPMiner: Mining ordered association rules with constraints. In Proceedings of the International Symposium on Intelligent Data Analysis (IDA), 2017 website
• Jonathan Rebane, Isak Karlsson, Lars Asker, Henrik Boström, and Panagiotis Papapetrou, Learning from Administrative Health Registries. In Proceedings of the Workshop on Data Science for Social Good (ECML/PKDD SoGood), 2017
• Isak Karlsson, Panagiotis Papapetrou, Lars Asker, Henrik Boström, and Hans E. Persson.. Mining disproportional itemsets for characterizing groups of heart failure patients from administrative health records. Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA), 2017
• Karlsson, I., Papapetrou, P. Boström, H., Generalized Random Shapelet Forests. In the Data Mining and Knowledge Discovery Journal (DAMI), 2016 (pdf)
• Henelius, A., Karlsson, I., Papapetrou. P., Ukkonnen, A., Puolamäki, K., Semigeometric Tiling of Event Sequences. In Proc. of the European Conference of Machine Learning and Principles and Practices of Knowledge Discovery in Databases (ECML PKDD), 2016
• Karlsson, I., Papapetrou, P. Boström, H., Early Random Shapelet Forest. In Proc. of the International Conference on Discovery Science (DS), Best Paper Award, 2016
• Karlsson, I., Boström, H. Predicting Adverse Drug Events using Heterogeneous Event Sequences, In Proc. of the International Conference on Healthcare Informatics (ICHI), 2016
• Karlsson, I., Papapetrou, P., Asker, L. Multi-channel ECG classification using forests of randomized shapelet trees In Proc. of the 7th International Conference on Pervasive Technologies Related to Assistive Environments, PETRA’15
• Alexios Kotsifakos, Isak Karlsson, Panagiotis Papapetrou, Vassilis Athitsos, and Dimitrios Gunopulos, Embedding-based Subsequence Matching with Gaps-Range-Tolerances: a Query-By-Humming application. In the Very Large Databases (VLDB) Journal (VLDBJ), 2015 (pdf)
• Karlsson, I., Bostrom, H., Papapetrou, P. Forests of Randomized Shapelet Trees In Proc. the 3rd International Symposium on Learning and Data Sciences (SLDS), 2015 (supplementary information, pdf)
• Henelius A., Puolam K., Karlsson I., Zhao J., Asker L., Boström H., Papapetrou, P. GoldenEye++: a Closer Look into the Black Box In Proc. the 3rd International Symposium on Learning and Data Sciences (SLDS), 2015 (pdf)
• Karlsson, I., Bostrom, H. Handling Sparsity with Random Forests when Predicting Adverse Drug Events from Electronic Health Records In Proc. the IEEE International Conference on Healthcare Informatics (ICHI), 2014 (pdf)
• Karlsson, I., Zhao, J. Dimensionality Reduction with Random Indexing: an application on adverse drug event detection using electronic health records. In Proc. of the 27th International Symposium On Computer-Based Medical Systems, In Press, 2014 (pdf)
• Asker, L., Boström, H., Karlsson, I., Papapetrou, P. and Zhao, J. Mining Candidates for Adverse Drug Interactions in Electronic Patient Records. In Proceedings of the 7th International Conference on Pervasive Technologies Related to Assistive Environments, PETRA’14, May 27-30, 2014, Island of Rhodes, Greece.
• Zhao, J., Karlsson, I., Asker, L. & Boström, H. Applying Methods for Signal Detection in Spontaneous Reports to Electronic Patient Records, KDD 2013 Workshop on Data Mining for Healtcare (DMH), 2013
• Karlsson, I., Zhao, J., Asker, L. & Boström, H. Predicting Adverse Drug Events By Analyzing Electronic Patient Records. In Proc. of the 14th Conference on Artificial Intelligence in Medicine (AIME), 2013