Randl, K., Pavlopoulos, I., Henriksson, A., Lindgren, T. (2024). Evaluating the Reliability of Self-Explanations in Large Language Models. To appear in Proc. of Discovery Science.
Wu, Y., Henriksson, A. (2024). Selecting from Multiple Strategies Improves the Foreseeable Reasoning of Tool-Augmented Large Language Models. To appear in Proc. of ECML-PKDD.
Randl, K, Pavlopoulos, I., Henriksson, A., Lindgren, T. (2024). CICLe: Conformal In-Context Learning for Largescale Multi-Class Food Risk Classification. In Findings of the Association for Computational Linguistics ACL 2024, pp. 7695–7715.
Li, X., Henriksson, A., Duneld, M., Nouri, J., Wu, Y. (2024). Supporting Teaching-to-the-Curriculum by Linking Diagnostic Tests to Curriculum Goals: Using Textbook Content as Context for Retrieval-Augmented Generation with Large Language Models. In Proc. of International Conference on AI in Education, pp. 118-132.
Vakili, T., Henriksson, A., Dalianis, H. (2024). End-to-End Pseudonymization of Fine-Tuned Clinical BERT Models: Privacy Preservation with Maintained Data Utility. In BMC Medical Informatics and Decision Making, 24(1), 162.
Vakili, T., Hullmann, T., Henriksson, A., Dalianis, H. (2024). When Is a Name Sensitive? Eponyms in Clinical Text and Implications for De-Identification. In Proc. of EACL, CALD-pseudo workshop.
Li, X., Henriksson, A., Duneld, M., Nouri, J., Wu, Y. (2024). Evaluating Embeddings from Pre-Trained Language Models and Knowledge Graphs for Educational Content Recommendation. In Future Internet.
Henriksson, A., Pawar, Y., Hedberg, P., Nauclér, P. (2023). Multimodal fine-tuning of clinical language models for predicting COVID-19 outcomes. In Artificial Intelligence in Medicine, 146.
Verkberk, J.D.M., van der Werrff, S.D., Weegar, R., Henriksson, A., Richir, M.C., van Mourik, M.S.M., Nauclér, P. (2023). The augmented value of using clinical notes in semi-automated surveillance of deep surgical site infections after colorectal surgery. In Antimicrobial Resistance & Infection Control, 12:117.
Lamproudis, A. & Henriksson, A. (2023). On the Impact of the Vocabulary for Domain-Adaptive Pretraining of Clinical Language Models. In International Joint Conference on Biomedical Engineering Systems and Technologies, pp. 315-332. Cham: Springer Nature Switzerland.
Valik, J.K., Ward, L., Tanushi, H., Johansson, A.F., Färnert, A., Mogensen, A.L., Pickering, B.W., Herasevich, V., Dalianis, H., Henriksson, A., Nauclér, P. (2023). Predicting sepsis onset using a machine learned causal probabilistic network algorithm based on electronic health records data. Scientific Reports, 13:117600.
Wu, Y., Henriksson, A., Duneld, M., Nouri, J. (2023). Towards Improving the Reliability and Transparency of ChatGPT for Educational Question Answering. In Proceedings of the Eighteenth European Conference on Technology Enhanced Learning (ECTEL).
Li, X., Henriksson, A., Nouri, J., Duneld, M., Yongchao, W. (2023). Linking Swedish Learning Materials to Exercises through an AI-enhanced Recommender System. In Proceedings of the 13th International Conference on Methodologies and Intelligent Systems for Technology Enhanced Learning (MIS4TEL).
Wu, Y., Henriksson, A., Nouri, J., Duneld, M., Li, X. (2023). Beyond Benchmarks: Spotting Key Topical Sentences While Improving Automated Essay Scoring Performance with Topic-Aware BERT. Electronics, 12, 150.
Wu, Y., Nouri, J., Megyesi, B., Henriksson, A., Duneld, M., Li, X. (2023). Towards Data-effective Educational Question Generation with Prompt-based Learning. In Proceedings of Computing Conference.
Lamproudis, A., Henriksson, A., Valik, J.K., Nauclér, P. (2022). Improving the Timeliness of Early Prediction Models for Sepsis through Utility Optimization. In Proceedings of IEEE International Conference on Tools with Artificial Intelligence (ICTAI).
Pawar, Y., Henriksson, A., Hedberg, P., Naucler, P. (2022). Leveraging Clinical BERT in Multimodal Mortality Prediction Models for COVID-19. In Proceedings of the 35th IEEE International Symposium on Computer-Based Medical Systems (CBMS), pp. 199-204.
Wu, Y., Henriksson, A., Nouri, J., Duneld, M., Li, X. (2022). Retrieving Key Topical Sentences With Topic-aware BERT when Conducting Automated Essay Scoring. In Proceedings of the 12th International Conference on Methodologies and Intelligent Systems for Technology Enhanced Learning (MIS4TEL).
Li, X., Nouri, J., Henriksson, A., Duneld, M., Wu, Y. (2022). Automatic Educational Concept Extraction Using NLP. In Proceedings of the 12th International Conference on Methodologies and Intelligent Systems for Technology Enhanced Learning (MIS4TEL).
Lamproudis, A., Henriksson, A., Dalianis, H. (2022). Evaluating Pretraining Strategies for Clinical BERT Models. In Proceedings of the 13th Conference on Language Resources and Evaluation (LREC), pp. 410-416.
Vakili, T., Lamproudis, A., Henriksson, A., Dalianis, H. (2022). Downstream Task Performance of BERT Models Pre-Trained Using Automatically De-Identified Clinical Data. In Proceedings of the 13th Conference on Language Resources and Evaluation (LREC), pp. 4245-4252.
van der Werff, S.D., Fritzing, M., Tanushi, H., Henriksson, A., Dalianis, H., Ternhag, A., Färnert, A., Nauclér, P. (2022). The accuracy of fully-automated algorithms for surveillance of healthcare-onset Clostridioides difficile infections in hospitalized patients. Antimicrobial Stewardship & Healthcare Epidemiology.
Lamproudis, A., Henriksson, A., Dalianis, H. (2022). Vocabulary Modifications for Domain-adaptive Pretraining of Clinical Language Models. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies – Volume 5: HEALTHINF, pp. 180-188.
Henriksson, A. Zdravkovic, J. (2021). Holistic Data-Driven Requirements Elicitation in the Big Data Era. Software and Systems Modeling.
Lamproudis, A., Henriksson, A., Dalianis, H. (2021). Developing a Clinical Language Model for Swedish: Continued Pretraining of Generic BERT with In-Domain Data. In Proc. of Recent Advances in Natural Language Processing (RANLP).
Xavier, F., Henriksson, A., Ralyté, J., Zdravkovic, J. (2021). Data-Driven Agile Requirements Elicitation through the Lenses of Situational Method Engineering. In Proc. of RE@Next!.
Valik, J.K., Mellhammar, L., Sundén-Cullberg, J., Ward, L., Unge, C., Dalianis, H., Henriksson, A., Strålin, K., Linder, A., Naucler, P. (2021). Peripheral oxygen saturation facilitates assessment of respiratory dysfunction in the Sequential Organ Failure Assessment Score with implications for the Sepsis-3 criteria. Critical Care Medicine.
van der Werff, S.D., Thiman, E., Tanushi, H., Valik, J.K, Henriksson, A., Ul Alam, M., Dalianis, H., Ternhag, A., Naucler, P (2021). The accuracy of fully-automated algorithms for surveillance of healthcare-associated urinary tract infections in hospitalized patients. Journal of Hospital Infection.
Ul Alam, M., Henriksson, A., Tanushi, H., Thiman, E., Naucler, P., Dalianis, H. (2021). Terminology Expansion with Prototype Embeddings: Extracting Symptoms of Urinary Tract Infection from Clinical Text. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies – Volume 5: HEALTHINF, pp. 47-57.
Berg, H., Henriksson, A., Fors, U., Dalianis, H. (2021). De-identification of Clinical Text for Secondary Use: Research Issues. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies – Volume 5: HEALTHINF, pp. 592-599
Lim, S., Henriksson, A., Zdravkovic, J. (2021). Data-driven Requirements Elicitation: A Systematic Literature Review. SN Computer Science, 2:16, pp. 1-35.
Berg, H., Henriksson, A., Dalianis, H. (2020). The Impact of De-identification on Downstream Named Entity Recognition in Clinical Text. In Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis (Louhi), pp. 1-11.
Henriksson, A., Zdravkovic, J. (2020). A Data-Driven Framework for Automated Requirements Elicitation from Heterogenous Digital Sources. In: The Practice of Enterprise Modeling. PoEM 2020. Lecture Notes in Business Information Processing, vol 400. Springer, Cham. https://doi.org/10.1007/978-3-030-63479-7_24.
Ul Alam, M., Henriksson, A., Valik, J.K., Ward, L., Naucler, P., Dalianis, H. (2020). Deep Learning from Heterogeneous Sequences of Sparse Medical Data for Early Prediction of Sepsis. In the proceedings of the 13th International Conference on Health Informatics HEALTHINF 2020, February 24-26, Valletta, Malta. Awarded Best Paper.
Valik, J.K, Ward, L., Tanushi, H., Müllersdorf, K., Ternhag, A., Aufwerber, E., Färnert, A., Johansson, A.F., Mogensen, M.L., Pickering, B., Dalianis, H., Henriksson, A., Herasevich, V., Nauclér, P. (2020). Validation of automated sepsis surveillance based on the Sepsis-3 clinical criteria against physician record review in a general hospital population: observational study using electronic health records data. BMJ Quality & Safety,
Henriksson, A., Kvist, M., Dalianis, H. (2017). Detecting Protected Health Information in Heterogeneous Clinical Notes. In Proceedings of MEDINFO, Hangzhou, China.
Henriksson, A., Kvist, M., Dalianis, H. (2017). Prevalence Estimation of Protected Health Information in Swedish Clinical Text. In Proceedings of Informatics for Health, Manchester, U.K.
Berndorfer, S., Henriksson, A. (2017). Automated Diagnosis Coding with Combined Text Representations. In Proceedings of Informatics for Health, Manchester, U.K.
Dziadek, J., Henriksson, A., Duneld, M. (2017). Improving Terminology Mapping in Clinical Text with Context-Sensitive Spelling Correction. In Proceedings of Informatics for Health, Manchester, U.K.
Ahltorp, M., Skeppstedt, M., Kitajima, S., Henriksson, A., Rzepka, R., Araki, K. (2016). Expansion of medical vocabularies using distributional semantics on Japanese patient blogs. Journal of Biomedical Semantics, 7:58.
Henriksson, A., Zhao, J., Dalianis, H., Boström, H. (2016). Ensembles of randomized trees using diverse distributed representations of clinical events. BMC Medical Informatics and Decision Making, 16(Suppl 2):69.
Zhao, J., Henriksson, A. (2016). Learning temporal weights of clinical events using variable importance. BMC Medical Informatics and Decision Making, 16(Suppl 2):71.
Grigonytė, G., Kvist, M., Wirén, M., Velupillai, S., Henriksson, A. (2016). Swedification patterns of Latin and Greek affixes in clinical text. Nordic Journal of Linguistics, 39(1): 5-37.
Henriksson, A. (2015). Ensembles of Semantic Spaces: On Combining Models of Distributional Semantics with Applications in Healthcare. Doctoral Thesis, Department of Computer and Systems Sciences, Stockholm University.
Zhao, J., Henriksson, A., Asker, L., Boström, H. (2015). Predictive modeling of structured electronic health records for adverse drug event detection. BMC Medical Informatics & Decision Making, Vol. 15, Suppl. 4.
Henriksson, A., Zhao, J., Boström, H., Dalianis, H. (2015). Modeling Electronic Health Records in Ensembles of Semantic Spaces for Adverse Drug Event Detection. In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington DC, USA.
Zhao, J., Henriksson, A, Kvist, M., Asker, L, Boström, H. (2015). Handling Temporality of Clinical Events for Drug Safety Surveillance. In Proceedings of the Annual Symposium of the American Medical Informatics Association (AMIA), San Francisco, USA.
Henriksson, A., Kvist, M., Dalianis, H., Duneld, M. (2015). Identifying adverse drug event information in clinical notes with distributional semantic representations of context. Journal of Biomedical Informatics, 57: 333-349.
Henriksson, A., Zhao, J., Boström, H., Dalianis, H. (2015). Modeling Heterogeneous Clinical Sequence Data in Semantic Space for Adverse Drug Event Detection. In Proceedings of IEEE International Conference on Data Science and Advanced Analytics (DSAA), Paris, France.
Zhao, J., Henriksson, A., Boström, H. (2015). Cascading Adverse Drug Event Detection in Electronic Health Records. In Proceedings of IEEE International Conference on Data Science and Advanced Analytics (DSAA), Paris, France.
Henriksson, A. (2015). Representing Clinical Notes for Adverse Drug Event Detection. In Proceedings of the Sixth International Workshop on Health Text Mining and Information Analysis (Louhi), Lisbon, Portugal.
Alfalahi, A., Skeppstedt, M., Ahlbom, R., Baskalayci, R., Henriksson, A., Asker, L., Paradis, C., Kerren, A. (2015). Expanding a dictionary of marker words for uncertainty and negation using distributional semantics. In Proceedings of the Sixth International Workshop on Health Text Mining and Information Analysis (Louhi), Lisbon, Portugal.
Henriksson, A. (2015). Learning Multiple Distributed Prototypes of Semantic Categories for Named Entity Recognition. International Journal of Data Mining and Bioinformatics, Vol. 13, No. 4, pp. 395-411.
Dalianis, H., Henriksson, A., Kvist, M., Velupillai, S., Weegar, R. (2015). HEALTH BANK – A Workbench for Data Science Applications in Healthcare. In Proceedings of CAiSE’15 – Industry Track, Stockholm, Sweden.
Henriksson, A., Dalianis, H., Kowalski, S. (2014). Generating Features for Named Entity Recognition by Learning Prototypes in Semantic Space: The Case of De-Identifying Health Records. In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Belfast, UK.
Zhao, J., Henriksson, A., Asker, L., Boström, H. (2014). Detecting Adverse Drug Events with Multiple Representations of Clinical Measurements. In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Belfast, UK.
Zhao, J., Henriksson, A., Boström, H. (2014). Detecting Adverse Drug Events Using Concept Hierarchies of Clinical Codes. In Proceedings of IEEE International Conference on Healthcare Informatics (ICHI), Verona, Italy.
Tengstrand, L., Megyesi, B., Henriksson, A., Duneld, M., Kvist, M. (2014). EACL — Expansion of Abbreviations in CLinical text. In Proceedings of the Workshop on Predicting and Improving Text Readability for Target Reader Populations (PITR), Gothenburg, Sweden.
Henriksson, A., Moen, H., Skeppstedt, M., Daudaravicius, V., Duneld, M. (2014). Synonym Extraction and Abbreviation Expansion with Ensembles of Semantic Spaces. Journal of Biomedical Semantics, 5:6.
Skeppstedt, M., Ahltorp, M., Henriksson, A. (2013). Vocabulary Expansion by Semantic Extraction of Medical Terms. In Proceedings of the 5th International Symposium on Languages in Biology and Medicine (LBM), Tokyo, Japan.
Henriksson, A. (2013). Semantic Spaces of Clinical Text — Leveraging Distributional Semantics for Natural Language Processing of Electronic Health Records. Licentiate Thesis of Philosophy, Department of Computer and Systems Sciences (DSV), Stockholm University.
Henriksson, A., Conway, M., Duneld, M., Chapman, W.W. (2013). Identifying Synonymy between SNOMED Clinical Terms of Varying Length Using Distributional Analysis of Electronic Health Records. In Proceedings of the Annual Symposium of the American Medical Informatics Association (AMIA), Washington DC, USA.
Henriksson, A., Skeppstedt, M., Kvist, M., Duneld, M., Conway, M. (2013). Corpus-Driven Terminology Development: Populating Swedish SNOMED CT with Synonyms Extracted from Electronic Health Records. In Proceedings of BioNLP, Sofia, Bulgaria.
Henriksson, A. & Hassel, M. (2013). Optimizing the Dimensionality of Clinical Term Spaces for Improved Diagnosis Coding Support. In Proceedings of Louhi Workshop on Health Document Text Mining and Information Analysis, Sydney, Australia.
Dalianis, H., Hassel, M., Henriksson, A. & Skeppstedt, M. (2012). Stockholm EPR Corpus: A Clinical Database Used to Improve Health Care. In Proceedings of Swedish Language Technology Conference (SLTC), pp. 17-18.
Henriksson, A., Moen, H., Skeppstedt, M., Eklund, A-M., Daudaravicius, V. & Hassel, M. (2012). Synonym Extraction of Medical Terms from Clinical Text Using Combinations of Word Space Models. In Proceedings of Semantic Mining in Biomedicine (SMBM), Zurich, Switzerland.
Henriksson, A., Kvist, M., Hassel, M. & Dalianis, H. (2012). Exploration of Adverse Drug Reactions in Semantic Vector Space Models of Clinical Text. In Proceedings of ICML Workshop on Machine Learning for Clinical Data Analysis, Edinburgh, UK.
Henriksson, A. & Hassel, M. (2011). Exploiting Structured Data, Negation Detection and SNOMED CT Terms in a Random Indexing Approach to Clinical Coding. In Proceedings of RANLP Workshop on Biomedical Natural Language Processing, Hissar, Bulgaria.
Henriksson, A. & Hassel, M. (2011). Election of Diagnosis Codes: Words as Responsible Citizens. In Proceedings of Louhi Workshop on Health Document Text Mining and Information Analysis, Bled, Slovenia.
Henriksson, A., Hassel, M. & Kvist, M. (2011). Diagnosis Code Assignment Support Using Random Indexing of Patient Records – A Qualitative Feasibility Study. In Proceedings of AIME, 13th Conference on Artificial Intelligence in Medicine, Bled, Slovenia.
Hassel, M., Henriksson, A. & Velupillai, S. (2011). Something Old, Something New – Applying a Pre-trained Parsing Model to Clinical Swedish. In Proceedings of NODALIDA – 18th Nordic Conference on Computational Linguistics, Riga, Latvia.
Henriksson, A. & Velupillai, S. (2010). Levels of Certainty in Knowledge-Intensive Corpora: An Initial Annotation Study. In Proceedings of the Workshop on Negation and Speculation in Natural Language Processing, ACL, pp 41-45, Uppsala, Sweden.
Henriksson, A. (2010). The Robustness of Knowledge: Analysis of Certainty in Narrative Knowledge Bases. Master thesis, KTH.