Papers by Lisa Raithel

4 papers
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient’s Perspective (2022.lrec-1)

Copied to clipboard

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.
Infherno: End-to-end Agent-based FHIR Resource Synthesis from Free-form Clinical Notes (2026.eacl-demo)

Copied to clipboard

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.
RecordTwin: Towards Creating Safe Synthetic Clinical Corpora (2025.findings-acl)

Copied to clipboard

Challenge: Existing methods to generate high-quality synthetic corpus from clinical documents require learning from the original clinical documents.
Approach: They propose a method to generate synthetic corpus from clinical documents using a large language model.
Outcome: The proposed method generates synthetic documents from in-hospital clinical documents.
A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages (2024.lrec-main)

Copied to clipboard

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 .

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations