Classification of Radiological Text in Small and Imbalanced Datasets in a Non-English Language
Rigshospitalet（哥本哈根大学医院（ Rigshospitalet））；Medical University of Innsbruck（因斯布鲁克医科大学）；Technical University of Denmark（丹麦技术大学）；University of Copenhagen（哥本哈根大学）
Vincent Beliveau, Helene Kaas, Martin Prener, Claes N. Ladefoged, Desmond Elliott, Gitte M. Knudsen, Lars H. Pinborg, Melanie Ganz
Natural language processing (NLP) in the medical domain can underperform in real-world applications involving small datasets in a non-English language with few labeled samples and imbalanced classes. There is yet no consensus on how to approach this problem. We evaluated a set of NLP models including BERT-like transformers, few-shot learning with sentence transformers (SetFit), and prompted large language models (LLM), using three datasets of radiology reports on magnetic resonance images of epilepsy patients in Danish, a low-resource language. Our results indicate that BERT-like models pretrained in the target domain of radiology reports currently offer the optimal performances for this scenario. Notably, the SetFit and LLM models underperformed compared to BERT-like models, with LLM performing the worst. Importantly, none of the models investigated was sufficiently accurate to allow for text classification without any supervision. However, they show potential for data filtering, which could reduce the amount of manual labeling required.
MOSAIC: A Multilingual, Taxonomy-Agnostic, and Computationally Efficient Approach for Radiological Report Classification
Department of Computer Science, University of Copenhagen（哥本哈根大学计算机科学系）；Neurobiology Research Unit, Copenhagen University Hospital（哥本哈根大学医院神经生物学研究单位）；Unumed Aps（Unumed公司）；Department of Diagnostic Radiology, Copenhagen University Hospital（哥本哈根大学医院诊断放射学系）；Department of Clinical Medicine, University of Copenhagen（哥本哈根大学临床医学系）；Cerebriu A/S（Cerebriu公司）；Institute for Human Genetics, Medical University of Innsbruck（因斯布鲁克医学大学人类遗传学研究所）
Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models
Nanyang Technological University（南洋理工大学）；DAMO Academy, Alibaba Group（阿里达摩院）；Hupan Lab（虎斑实验室）；National University of Singapore（新加坡国立大学）；Shanda AI Research Institute（沙达AI研究院）
MKG-Rank: Enhancing Large Language Models with Knowledge Graph for Multilingual Medical Question Answering
University of Tokyo（东京大学）；Texas A&M University（德克萨斯农工大学）；Duke-NUS Medical School（杜克-新加坡国立大学医学院）；Smartor LLC（斯马特有限责任公司）；NEC Laboratories America（美国电气公司实验室）；University of Geneva（日内瓦大学）
Large Language Models Leverage External Knowledge to Extend Clinical Insight Beyond Language Boundaries
School of Public Health, Zhejiang University School of Medicine（浙江大学医学院公共卫生学院）；Jarvis Research Center, Tencent YouTu Lab（腾讯优图实验室Jarvis研究中心）；Harvard T.H. Chan School of Public Health（哈佛大学陈曾熙公共卫生学院）；Harvard Medical School（哈佛医学院）
Language on Demand, Knowledge at Core: Composing LLMs with Encoder-Decoder Translation Models for Extensible Multilinguality
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences（智能信息处理重点实验室，计算技术研究所，中国科学院）；State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences（人工智能安全国家重点实验室，计算技术研究所，中国科学院）；University of Chinese Academy of Sciences, Beijing, China（中国科学院大学，北京，中国）
Advancing Equitable AI: Evaluating Cultural Expressiveness in LLMs for Latin American Contexts
Department of Applied Computing, Michigan Technological University, Houghton, MI, USA（应用计算系，密歇根技术大学，霍顿，密歇根州，美国）；Department of Psychology and Human Factors, Michigan Technological University, Houghton, MI, USA（心理学与人因学系，密歇根技术大学，霍顿，密歇根州，美国）
A Knowledge-Informed Large Language Model Framework for U.S. Nuclear Power Plant Shutdown Initiating Event Classification for Probabilistic Risk Assessment
University of Idaho（爱达荷大学）；Idaho National Laboratory（爱达荷国家实验室）
CLEAR: Cross-Lingual Enhancement in Alignment via Reverse-training
Department of Computer Science and Engineering, Korea University（韩国大学计算机科学与工程系）；Department of English Language and Literature, Kyungpook National University（庆北国立大学英语语言文学系）
