Table of Contents

• Frontmatter [doi]
• Multi-Source (Pre-)Training for Cross-Domain Measurement, Unit and Context ExtractionYueling Li, Sebastian Martschat, Simone Paolo Ponzetto. 1-25 [doi]
• Gaussian Distributed Prototypical Network for Few-shot Genomic Variant DetectionJiarun Cao, Niels Peek, Andrew G. Renehan, Sophia Ananiadou. 26-36 [doi]
• Exploring Partial Knowledge Base Inference in Biomedical Entity LinkingHongyi Yuan, Keming Lu, Zheng Yuan 0002. 37-49 [doi]
• Boosting Radiology Report Generation by Infusing Comparison PriorSanghwan Kim, Farhad Nooralahzadeh, Morteza Rohanian, Koji Fujimoto, Mizuho Nishio, Ryo Sakamoto, Fabio Rinaldi 0001, Michael Krauthammer. 50-61 [doi]
• Using Bottleneck Adapters to Identify Cancer in Clinical Notes under Low-Resource ConstraintsOmid Rohanian, Hannah Jauncey, Mohammadmahdi Nouriborji, Vinod Kumar, Bronner P. Gonçalves, Christiana Kartsonaki, Isaric Clinical Characterisation Group, Laura Merson, David A. Clifton. 62-78 [doi]
• Evaluating and Improving Automatic Speech Recognition using SeverityRyan Whetten, Casey Kennington. 79-91 [doi]
• Zero-shot Temporal Relation Extraction with ChatGPTChenhan Yuan, Qianqian Xie, Sophia Ananiadou. 92-102 [doi]
• Good Data, Large Data, or No Data? Comparing Three Approaches in Developing Research Aspect Classifiers for Biomedical PapersShreya Chandrasekhar, Chieh-Yang Huang, Ting-Hao K. Huang. 103-113 [doi]
• Sentiment-guided Transformer with Severity-aware Contrastive Learning for Depression Detection on Social MediaTianlin Zhang, Kailai Yang, Sophia Ananiadou. 114-126 [doi]
• Exploring Drug Switching in Patients: A Deep Learning-based Approach to Extract Drug Changes and Reasons from Social MediaMourad Sarrouti, Carson Tao, Yoann Mamy Randriamihaja. 127-132 [doi]
• Is the ranking of PubMed similar articles good enough? An evaluation of text similarity methods for three datasetsMariana L. Neves, Ines Schadock, Beryl Eusemann, Gilbert Schönfelder, Bettina Bert, Daniel Butzke. 133-144 [doi]
• How Much do Knowledge Graphs Impact Transformer Models for Extracting Biomedical Events?Laura Zanella, Yannick Toussaint. 145-155 [doi]
• An end-to-end neural model based on cliques and scopes for frame extraction in long breast radiology reportsPerceval Wajsbürt, Xavier Tannier. 156-170 [doi]
• DISTANT: Distantly Supervised Entity Span Detection and ClassificationKen Yano, Makoto Miwa, Sophia Ananiadou. 171-177 [doi]
• Large Language Models as Instructors: A Study on Multilingual Clinical Entity ExtractionSimon Meoni, Éric de la Clergerie, Théo Ryffel. 178-190 [doi]
• Event-independent temporal positioning: application to French clinical textNesrine Bannour, Bastien Rance, Xavier Tannier, Aurélie Névéol. 191-205 [doi]
• ADEQA: A Question Answer based approach for joint ADE-Suspect Extraction using Sequence-To-Sequence TransformersVinayak Arannil, Tomal Deb, Atanu Roy. 206-214 [doi]
• Privacy Aware Question-Answering System for Online Mental Health Risk AssessmentPrateek Chhikara, Ujjwal Pasupulety, John Marshall, Dhiraj Chaurasia, Shweta Kumari. 215-222 [doi]
• AliBERT: A Pre-trained Language Model for French Biomedical TextAman Berhe, Guillaume Draznieks, Vincent Martenot, Valentin Masdeu, Lucas Davy, Jean-Daniel Zucker. 223-236 [doi]
• Multiple Evidence Combination for Fact-Checking of Health-Related InformationPritam Deka, Anna Jurek-Loughrey, Deepak P 0001. 237-247 [doi]
• Building a Corpus for Biomedical Relation Extraction of Species MentionsOumaima El Khettari, Solen Quiniou, Samuel Chaffron. 248-254 [doi]
• Automated Extraction of Molecular Interactions and Pathway Knowledge using Large Language Model, Galactica: Opportunities and ChallengesGilchan Park, Byung-Jun Yoon, Xihaier Luo, Vanessa López-Marrero, Patrick R. Johnstone, Shinjae Yoo, Francis J. Alexander. 255-264 [doi]
• Automatic Glossary of Clinical Terminology: a Large-Scale Dictionary of Biomedical Definitions Generated from Ontological KnowledgeFrançois Remy, Kris Demuynck, Thomas Demeester. 265-272 [doi]
• Comparing and combining some popular NER approaches on Biomedical tasksHarsh Verma, Sabine Bergler, Narjesossadat Tahaei. 273-279 [doi]
• Extracting Drug-Drug and Protein-Protein Interactions from Text using a Continuous Update of Tree-TransformersSudipta Singha Roy, Robert E. Mercer. 280-291 [doi]
• Resolving Elliptical Compounds in German Medical TextNiklas Kammer, Florian Borchert, Silvia Winkler, Gerard de Melo, Matthieu-P. Schapranow. 292-305 [doi]
• Augmenting Reddit Posts to Determine Wellness Dimensions impacting Mental HealthChandreen Liyanage, Muskan Garg, Vijay Mago, Sunghwan Sohn. 306-312 [doi]
• End-to-end clinical temporal information extraction with multi-head attentionTimothy A. Miller, Steven Bethard, Dmitriy Dligach, Guergana Savova. 313-319 [doi]
• Intermediate Domain Finetuning for Weakly Supervised Domain-adaptive Clinical NERShilpa Suresh, Nazgol Tavabi, Shahriar Golchin, Leah Gilreath, Rafael Garcia-Andujar, Alexander Kim, Joseph Murray, Blake Bacevich, Ata Kiapour. 320-325 [doi]
• Evaluation of ChatGPT on Biomedical Tasks: A Zero-Shot Comparison with Fine-Tuned Generative TransformersIsrat Jahan, Md. Tahmid Rahman Laskar, Chun Peng, Jimmy X. Huang. 326-336 [doi]
• BIOptimus: Pre-training an Optimal Biomedical Language Model with Curriculum Learning for Named Entity RecognitionVera Pavlova, Mohammed Makhlouf. 337-349 [doi]
• Biomedical Language Models are Robust to Sub-optimal TokenizationBernal Jimenez Gutierrez, Huan Sun 0001, Yu Su 0001. 350-362 [doi]
• Distantly Supervised Document-Level Biomedical Relation Extraction with Neighborhood Knowledge GraphsTakuma Matsubara, Makoto Miwa, Yutaka Sasaki. 363-368 [doi]
• BioNART: A Biomedical Non-AutoRegressive Transformer for Natural Language GenerationMasaki Asada, Makoto Miwa. 369-376 [doi]
• Biomedical Relation Extraction with Entity Type Markers and Relation-specific Question AnsweringKoshi Yamada, Makoto Miwa, Yutaka Sasaki. 377-384 [doi]
• Biomedical Document Classification with Literature Graph Representations of Bibliographies and EntitiesRyuki Ida, Makoto Miwa, Yutaka Sasaki. 385-395 [doi]
• Zero-Shot Information Extraction for Clinical Meta-Analysis using Large Language ModelsDavid Kartchner, Selvi Ramalingam, Irfan Al-Hussaini, Olivia Kronick, Cassie S. Mitchell. 396-405 [doi]
• Can Social Media Inform Dietary Approaches for Health Management? A Dataset and Benchmark for Low-Carb DietSkyler Zou, Xiang Dai, Grant Brinkworth, Pennie Taylor, Sarvnaz Karimi. 406-412 [doi]
• Promoting Fairness in Classification of Quality of Medical EvidenceSimon Suster, Timothy Baldwin, Karin Verspoor. 413-426 [doi]
• WeLT: Improving Biomedical Fine-tuned Pre-trained Language Models with Cost-sensitive LearningGhadeer Mobasher, Wolfgang Mller, Olga Krebs, Michael Gertz 0001. 427-438 [doi]
• Hospital Discharge Summarization Data ProvenancePaul Landes, Aaron Chaise, Kunal Patel, Sean S. Huang, Barbara Di Eugenio. 439-448 [doi]
• RadAdapt: Radiology Report Summarization via Lightweight Domain Adaptation of Large Language ModelsDave Van Veen, Cara Van Uden, Maayane Attias, Anuj Pareek, Christian Bluethgen, Malgorzata Polacin, Wah Chiu, Jean-Benoit Delbrouck, Juan Manuel Zambrano Chaves, Curtis P. Langlotz, Akshay Chaudhari, John M. Pauly. 449-460 [doi]
• Overview of the Problem List Summarization (ProbSum) 2023 Shared Task on Summarizing Patients' Active Diagnoses and Problems from Electronic Health Record Progress NotesYanjun Gao, Dmitriy Dligach, Timothy Miller 0002, Majid Afshar. 461-467 [doi]
• BioLaySumm 2023 Shared Task: Lay Summarisation of Biomedical Research ArticlesTomas Goldsack, Zheheng Luo, Qianqian Xie, Carolina Scarton, Matthew Shardlow, Sophia Ananiadou, Chenghua Lin. 468-477 [doi]
• Overview of the RadSum23 Shared Task on Multi-modal and Multi-anatomical Radiology Report SummarizationJean-Benoit Delbrouck, Maya Varma, Pierre J. Chambon, Curtis P. Langlotz. 478-482 [doi]
• GRASUM at BioLaySumm Task 1: Background Knowledge Grounding for Readable, Relevant, and Factual Biomedical Lay SummariesDomenic Rosati. 483-490 [doi]
• DeakinNLP at ProbSum 2023: Clinical Progress Note Summarization with Rules and Language ModelsClinical Progress Note Summarization with Rules and Languague ModelsMing Liu, Dan Zhang, Weicong Tan, He Zhang. 491-496 [doi]
• TALP-UPC at ProbSum 2023: Fine-tuning and Data Augmentation Strategies for NERNeil Torrero, Gerard Sant, Carlos Escolano. 497-502 [doi]
• Team: PULSAR at ProbSum 2023: PULSAR: Pre-training with Extracted Healthcare Terms for Summarising Patients' Problems and Data Augmentation with Black-box Large Language ModelsHao Li, Yu Ping Wu, Viktor Schlegel, Riza Batista-Navarro, Thanh Tung Nguyen, Abhinav Ramesh Kashyap, Xiao-Jun Zeng, Daniel Beck, Stefan Winkler 0001, Goran Nenadic. 503-509 [doi]
• Team Converge at ProbSum 2023: Abstractive Text Summarization of Patient Progress NotesGaurav Kolhatkar, Aditya Paranjape, Omkar Gokhale, Dipali Kadam. 510-515 [doi]
• CUED at ProbSum 2023: Hierarchical Ensemble of Summarization ModelsPotsawee Manakul, Yassir Fathullah, Adian Liusie, Vyas Raina, Vatsal Raina, Mark J. F. Gales. 516-523 [doi]
• ELiRF-VRAIN at BioNLP Task 1B: Radiology Report SummarizationVicent Ahuir Esteve, Encarna Segarra, Lluís F. Hurtado. 524-529 [doi]
• SINAI at RadSum23: Radiology Report Summarization Based on Domain-Specific Sequence-To-Sequence Transformer ModelMariia Chizhikova, Manuel Carlos Díaz-Galiano, Luis Alfonso Ureña López, María-Teresa Martín Valdivia. 530-534 [doi]
• KnowLab at RadSum23: comparing pre-trained language models in radiology report summarizationJinge Wu, Daqian Shi, Abul Hasan, Honghan Wu. 535-540 [doi]
• nav-nlp at RadSum23: Abstractive Summarization of Radiology Reports using BART FinetuningSri Macharla, Ashok Madamanchi, Nikhilesh Kancharla. 541-544 [doi]
• e-Health CSIRO at RadSum23: Adapting a Chest X-Ray Report Generator to Multimodal Radiology Report SummarisationAaron Nicolson, Jason Dowling, Bevan Koopman. 545-549 [doi]
• shs-nlp at RadSum23: Domain-Adaptive Pre-training of Instruction-tuned LLMs for Radiology Report Impression GenerationSanjeev Kumar Karn, Rikhiya Ghosh, Kusuma P, Oladimeji Farri. 550-556 [doi]
• UTSA-NLP at RadSum23: Multi-modal Retrieval-Based Chest X-Ray Report SummarizationTongnian Wang, Xingmeng Zhao, Anthony Rios. 557-566 [doi]
• KU-DMIS-MSRA at RadSum23: Pre-trained Vision-Language Model for Radiology Report SummarizationGangwoo Kim, Hajung Kim, Lei Ji 0001, Seongsu Bae, Chanhwi Kim, Mujeen Sung, Hyunjae Kim, Kun Yan, Eric Chang, Jaewoo Kang. 567-573 [doi]
• VBD-NLP at BioLaySumm Task 1: Explicit and Implicit Key Information Selection for Lay Summarization on Biomedical Long DocumentsPhuc Phan, Tri Tran, Hai-Long Trieu. 574-578 [doi]
• APTSumm at BioLaySumm Task 1: Biomedical Breakdown, Improving Readability by Relevancy Based SelectionA. s. Poornash, Atharva Deshmukh, Archit Sharma, Sriparna Saha. 579-585 [doi]
• NCUEE-NLP at BioLaySumm Task 2: Readability-Controlled Summarization of Biomedical Articles Using the PRIMERA ModelsChao-Yi Chen, Jen-Hao Yang, Lung-Hao Lee. 586-591 [doi]
• Pathology Dynamics at BioLaySumm: the trade-off between Readability, Relevance, and Factuality in Lay SummarizationIrfan Al-Hussaini, Austin Wu, Cassie S. Mitchell. 592-601 [doi]
• IKM_Lab at BioLaySumm Task 1: Longformer-based Prompt Tuning for Biomedical Lay Summary GenerationYu-Hsuan Wu, Ying-Jia Lin, Hung-Yu Kao. 602-610 [doi]
• MDC at BioLaySumm Task 1: Evaluating GPT Models for Biomedical Lay SummarizationOisn Turbitt, Robert Bevan, Mouhamad Aboshokor. 611-619 [doi]
• LHS712EE at BioLaySumm 2023: Using BART and LED to summarize biomedical research articlesQuancheng Liu, Xiheng Ren, V. G. Vinod Vydiswaran. 620-624 [doi]
• IITR at BioLaySumm Task 1: Lay Summarization of BioMedical articles using TransformersVenkat praneeth Reddy, Pinnapu Reddy Harshavardhan Reddy, Karanam Sai Sumedh, Raksha Sharma. 625-628 [doi]
• CSIRO Data61 Team at BioLaySumm Task 1: Lay Summarisation of Biomedical Research Articles Using Generative ModelsMong Yuan Sim, Xiang Dai, Maciej Rybinski, Sarvnaz Karimi. 629-635 [doi]
• ISIKSumm at BioLaySumm Task 1: BART-based Summarization System Enhanced with Bio-Entity LabelsCagla Colak, Lknur Karadeniz. 636-640 [doi]