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Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI)

Authors: Islamaj, Rezarta; Lima López, Salvador; Xu, Dongfang; Al-Nabki, Mhd Wesam; Chan, Joey; Krallinger, Martin; Gonzalez Hernandez, Graciela; +1 Authors

Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI)

Abstract

Table of Contents 1. The BioCreative IX Challenge and Workshop: Large Language Models for Clinical and Biomedical NLP. Rezarta Islamaj, Salvador Lima-López, Dongfang Xu, Wesam Al-Nabki, Joey Chan, Martin Krallinger, Graciela González Hernández and Zhiyong Lu. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF Workshop Papers 2. Integrating Text and Time-Series into (Large) Language Models to Predict Medical Outcomes. Iyadh Ben Cheikh Larbi, Ajay Madhavan Ravichandran, Aljoscha Burchardt and Roland Roller. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 3. Open-LBP-RF: A Clinical Note Dataset annotated with Lower Back Pain Risk Factors. Aman Jaiswal, Alan Katz and Evangelos Milios. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 4. Detecting Medication Mentions in Social Media Data Using Large Language Models. Guillermo Lopez-Garcia, Dongfang Xu and Graciela Gonzalez-Hernandez. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 5. Reasoning Large Language Models for Clinical Coding. Akram Mustafa, Usman Naseem and Mostafa Rahimi Azghadi. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 6. Enhancing BERT Performance with LLMs: Structured Data Augmentation for Biomedical Entity Recognition. Ying Wei, Qi Li and Jay Pillai. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 7. Enhancing Health Fact-Checking with LLM-Generated Synthetic Data. Jingze Zhang, Jiahe Qian, Yiliang Zhou and Yifan Peng. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF MedHopQA Shared Task 8. Overview of the MedHopQA track at BioCreative IX: track description, participation and evaluation of systems for multi-hop medical question answering. Rezarta Islamaj, Joey Chan, Robert Leaman and Zhiyong Lu. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 9. The corpus of the MedHopQA track at BioCreative IX. Rezarta Islamaj, Robert Leaman, Joey Chan and Zhiyong Lu. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 10. DMIS Lab at MedHopQA-2025: Ensemble Multi-Retrieval Methodologies with Reasoning Language Model Decision. Jongmyung Jung, Hyeongsoon Hwang, Yein Park, Minju Song, Jaehoon Yoon, Hyeon Hwang, Sanghoon Lee, Jiwoong Sohn and Jaewoo Kang. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 11. UETQuintet at BioCreative IX – MedHopQA: Enhancing Biomedical QA with Selective Multi-hop Reasoning and Contextual Retrieval. Quoc-An Nguyen, Thi-Minh-Thu Vu, Bich-Dat Nguyen, Dinh-Quang-Minh Tran and Hoang-Quynh Le. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 12. CaresAI at BioCreative IX Track 1 - LLM for Biomedical QA. Reem Abdel-Salam, Mary Adewunmi and Modinat A. Abayomi. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 13. Agentic and Non-Agentic Multi-Hop Systems for Medical Question Answering. Harikrishnan Gurushankar Saisudha, Ganesh Chandrasekar and Sabine Bergler. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 14. NHSRAG: Addressing Multi-Hop Medical QA with Named-entity Heuristic Search Retrieval-Augmented Generation. Pakawat Phasook, Rapepong Pitijaroonpong, Jiramet Kinchagawat, Amrest Chinkamol, Tossaporn Saengja, Jitkapat Sawatphol and Piyalitt Ittichaiwong. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 15. lasigeBioTM at MedHop track : Can a Lean RAG-Enhanced Model Compete with MedGemma?. Sofia I. R. Conceição, Paulo R. C. Lopes and Francisco M. Couto. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 16. Wikipedia-based hybrid-search RAG with prompt decomposition for MedHopQA. Rustam R. Taktashov, Nadezhda Yu. Bizyukova, Olga A. Tarasova and Alexander V. Dmitriev. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 17. DeepRAG: Integrating Hierarchical Reasoning and Process Supervision for Biomedical Multi-Hop QA. Yuelyu Ji, Hang Zhang, Shiven Verma, Hui Ji, Chun Li, Yushui Han and Yanshan Wang. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 18. Evaluating Advanced Prompting on Gemini Flash for Multi-Hop Biomedical QA. Ahmed Bajaber and Mohammed Alliheedi. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF ToxHabits Shared Task 19. Overview of ToxHabits at BioCreative IX: corpus, guidelines and evaluation of systems for the detection of Toxic Habits from text. Wesam Al-Nabki, Salvador Lima-López, Gabriel Vayá-Abad and Martin Krallinger. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 20. Biomedical Named Entity Recognition for Substance Abuse: Using BERT-CRF and Large Language Models for Spanish Clinical Data. Nadezhda Yu. Biziukova, Rustam R. Taktashov, Alexander V. Dmitriev and Olga A. Tarasova. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 21. ICB-UMA at BioCreative IX 2025 Track 3 - ToxHabits: Named Entity Recognition for Detection of Substance Use and Abuse in Clinical Texts. Fernando Gallego and Francisco J. Veredas. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 22. NOWJ @BioCreative IX ToxHabits: An Ensemble Deep Learning Approach for Detecting Substance Use and Contextual Information in Clinical Texts. Huu-Huy-Hoang Tran, Gia-Bao Duong, Quoc-Viet-Anh Tran, Thi-Hai-Yen Vuong and Hoang-Quynh Le. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 23. SINAI Team at ToxHabits: Toxic Habit Extraction with EuroBERT and Instruction-Tuned Language Models. Lucas Molino-Piñar, María Teresa Martín-Valdivia and Manuel Carlos Díaz-Galiano. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF 24. FMI@SU ToxHabits: Evaluating LLMs Performance on Toxic Habit Extraction in Spanish Clinical Texts. Sylvia Vassileva, Ivan Koychev and Svetla Boytcheva. Proceedings of the BioCreative IX Challenge and Workshop (BC9): Large Language Models for Clinical and Biomedical NLP at the International Joint Conference on Artificial Intelligence (IJCAI), XX-XX. PDF

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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