Papers by Roland Roller
Clinical Text Anonymization, its Influence on Downstream NLP Tasks and the Risk of Re-Identification (2023.eacl-srw)
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| Challenge: | De-identification and anonymization of clinical data is needed to solve access to clinicaldata. |
| Approach: | They propose to use text anonymization techniques to break the anonymization of clinical data . they propose to apply a re-identification attack to the anonymized text data to break this. |
| Outcome: | The proposed approach can break the anonymization of clinical data, the authors show . |
From Witch’s Shot to Music Making Bones - Resources for Medical Laymen to Technical Language and Vice Versa (2020.lrec-1)
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| Challenge: | Information we share online unveils directly or indirectly information about our lifestyle and health situation. |
| Approach: | They propose a dataset which annotates medical laymen and technical expressions in a patient forum and a set of medical synonyms and definitions. |
| Outcome: | The proposed dataset annotates medical laymen and technical expressions in a patient forum along with a set of medical synonyms and definitions. |
Subjective Text Complexity Assessment for German (2022.lrec-1)
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| Challenge: | Often, readability is defined as how easily a written text is to read. |
| Approach: | They propose to use a corpus of sentences provided by a German IT service provider to assess the readability of German text. |
| Outcome: | The proposed model can predict complexity of German text by using linguistically motivated features. |
An Annotated Corpus of Textual Explanations for Clinical Decision Support (2022.lrec-1)
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Roland Roller, Aljoscha Burchardt, Nils Feldhus, Laura Seiffe, Klemens Budde, Simon Ronicke, Bilgin Osmanodja
| Challenge: | In recent years, machine learning for clinical decision support has gained more and more attention. |
| Approach: | They propose to use XAI to provide an explanation of a model's decision making process by constructing a corpus of sentences that are annotated with different semantic layers. |
| Outcome: | The proposed models outperform physicians on very specific, narrow tasks or can help physicians to work more efficiently. |
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient’s Perspective (2022.lrec-1)
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| Challenge: | a recent study shows that the class labels of german documents containing ADRs are imbalanced . clinical trials and physicians prescribing medications cannot cover every potential use case. |
| Approach: | They propose to use binary annotated documents from a german patient forum to detect ADRs. |
| Outcome: | The proposed model achieves an F1 score of 37.52 for the positive class on the German patient forum. |
Mitigating Bias in Item Retrieval for Enhancing Exam Assembly in Vocational Education Services (2025.naacl-industry)
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| Challenge: | Despite the practical importance of exam assembly, few methods exist to support educators during manual item retrieval for exam assembly tasks. |
| Approach: | They propose a mixed-integer programming re-ranking approach to improve relevance while mitigating bias on an industry-grade exam assembly platform. |
| Outcome: | The proposed approach improves relevance and reduces bias by 17% when compared to other methods on a real-world exam assembly platform. |
Infherno: End-to-end Agent-based FHIR Resource Synthesis from Free-form Clinical Notes (2026.eacl-demo)
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| Challenge: | HL7 FHIR format is a desirable format for clinical data integration and healthcare services. |
| Approach: | They propose an end-to-end framework that adheres to the HL7 FHIR document schema . it uses LLM agents, code execution, and healthcare terminology database tools . |
| Outcome: | The proposed framework adheres to the HL7 FHIR document schema and competes well with a human baseline in predicting FHIr resources from unstructured text. |
A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages (2024.lrec-main)
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Lisa Raithel, Hui-Syuan Yeh, Shuntaro Yada, Cyril Grouin, Thomas Lavergne, Aurélie Névéol, Patrick Paroubek, Philippe Thomas, Tomohiro Nishiyama, Sebastian Möller, Eiji Aramaki, Yuji Matsumoto, Roland Roller, Pierre Zweigenbaum
| Challenge: | Existing clinical corpora mostly revolves around scientific articles in English . existing literature is limited to only a few scientific articles . |
| Approach: | They propose to use user-generated data sources to uncover adverse drug reactions . existing clinical corpora mostly revolves around scientific articles in english . authors provide statistics to highlight certain challenges associated with the corpus . |
| Outcome: | The proposed corpus includes 12 entity types, four attribute types, and 13 relation types . it provides strong baselines for extracting entities and relations between entities . |