| Using rule-based natural language processing to improve disease normalization in biomedical text N Kang, B Singh, Z Afzal, EM van Mulligen, JA Kors Journal of the American Medical Informatics Association 20 (5), 876-881, 2013 | 162 | 2013 |
| Knowledge-based extraction of adverse drug events from biomedical text N Kang, B Singh, C Bui, Z Afzal, EM van Mulligen, JA Kors BMC bioinformatics 15, 1-8, 2014 | 108 | 2014 |
| Improving sensitivity of machine learning methods for automated case identification from free-text electronic medical records Z Afzal, MJ Schuemie, JC van Blijderveen, EF Sen, MCJM Sturkenboom, ... BMC medical informatics and decision making 13, 1-11, 2013 | 69 | 2013 |
| ContextD: an algorithm to identify contextual properties of medical terms in a Dutch clinical corpus Z Afzal, E Pons, N Kang, MCJM Sturkenboom, MJ Schuemie, JA Kors BMC bioinformatics 15, 1-12, 2014 | 55 | 2014 |
| Automatic generation of case‐detection algorithms to identify children with asthma from large electronic health record databases Z Afzal, M Engelkes, KMC Verhamme, HM Janssens, MCJM Sturkenboom, ... Pharmacoepidemiology and drug safety 22 (8), 826-833, 2013 | 52 | 2013 |
| Using an ensemble system to improve concept extraction from clinical records N Kang, Z Afzal, B Singh, EM Van Mulligen, JA Kors Journal of biomedical informatics 45 (3), 423-428, 2012 | 47 | 2012 |
| Erasmus MC at CLEF eHealth 2016: Concept recognition and coding in French texts EM Van Mulligen, Z Afzal, S Akhondi, D Vo, J Kors | 42 | 2016 |
| Chemu 2020: Natural language processing methods are effective for information extraction from chemical patents J He, DQ Nguyen, SA Akhondi, C Druckenbrodt, C Thorne, R Hoessel, ... Frontiers in Research Metrics and Analytics 6, 654438, 2021 | 41 | 2021 |
| Extraction of chemical-induced diseases using prior knowledge and textual information E Pons, BFH Becker, SA Akhondi, Z Afzal, EM Van Mulligen, JA Kors Database 2016, baw046, 2016 | 38 | 2016 |
| Overview of ChEMU 2020: named entity recognition and event extraction of chemical reactions from patents J He, DQ Nguyen, SA Akhondi, C Druckenbrodt, C Thorne, R Hoessel, ... Experimental IR Meets Multilinguality, Multimodality, and Interaction: 11th …, 2020 | 37 | 2020 |
| Chemical entity recognition in patents by combining dictionary-based and statistical approaches SA Akhondi, E Pons, Z Afzal, H van Haagen, BFH Becker, KM Hettne, ... Database 2016, baw061, 2016 | 25 | 2016 |
| An extended overview of the CLEF 2020 ChEMU lab: information extraction of chemical reactions from patents J He, DQ Nguyen, SA Akhondi, C Druckenbrodt, C Thorne, R Hoessel, ... Proceedings of the CLEF 2020 conference, 2020 | 19 | 2020 |
| RELigator: Chemical-disease relation extraction using prior knowledge and textual information E Pons, B Becker, SA Akhondi, Z Afzal, EM van Mulligen, JA Kors Proceedings of the Fifth BioCreative Challenge Evaluation Workshop, 247-253, 2015 | 19 | 2015 |
| Erasmus MC approaches to the i2b2 Challenge N Kang, RJ Barendse, Z Afzal, B Singh, MJ Schuemie, EM van Mulligen, ... Proceedings of the 2010 i2b2/VA workshop on challenges in natural language …, 2010 | 18 | 2010 |
| Biomedical Concept Recognition in French Text Using Automatic Translation of English Terms. Z Afzal, SA Akhondi, H van Haagen, EM van Mulligen, JA Kors CLEF (Working Notes), 2015 | 15 | 2015 |
| A framework to automatically extract funding information from text S Kayal, Z Afzal, G Tsatsaronis, M Doornenbal, S Katrenko, M Gregory Machine Learning, Optimization, and Data Science: 4th International …, 2019 | 10 | 2019 |
| ChEMU 2021: reaction reference resolution and anaphora resolution in chemical patents J He, B Fang, H Yoshikawa, Y Li, SA Akhondi, C Druckenbrodt, C Thorne, ... Advances in Information Retrieval: 43rd European Conference on IR Research …, 2021 | 8 | 2021 |
| Tagging funding agencies and grants in scientific articles using sequential learning models S Kayal, Z Afzal, G Tsatsaronis, S Katrenko, P Coupet, M Doornenbal, ... BioNLP 2017, 216-221, 2017 | 7 | 2017 |
| Generating and evaluating a propensity model using textual features from electronic medical records Z Afzal, GMC Masclee, MCJM Sturkenboom, JA Kors, MJ Schuemie Plos one 14 (3), e0212999, 2019 | 6 | 2019 |
| Text mining to support knowledge discovery from electronic health records Z Afzal | 6 | 2018 |
Jan KorsErasmus University Medical CenterVerified email at erasmusmc.nl
