Classifying Long Clinical Documents with Pre-trained Transformers
University of Arizona（亚利桑那大学）；Boston Children’s Hospital（波士顿儿童医院）；Harvard Medical School（哈佛医学院）；University of Wisconsin–Madison（威斯康星大学麦迪逊分校）；Loyola University Chicago（芝加哥洛约拉大学）
Xin Su, Timothy Miller, Xiyu Ding, Majid Afshar, Dmitriy Dligach
Automatic phenotyping is a task of identifying cohorts of patients that match a predefined set of criteria. Phenotyping typically involves classifying long clinical documents that contain thousands of tokens. At the same time, recent state-of-art transformer-based pre-trained language models limit the input to a few hundred tokens (e.g. 512 tokens for BERT). We evaluate several strategies for incorporating pre-trained sentence encoders into document-level representations of clinical text, and find that hierarchical transformers without pre-training are competitive with task pre-trained models.
Large language models are vulnerable to incidental information in clinical documentation and reasoning
NYU Langone Health（纽约大学朗格尼健康中心）；Johns Hopkins University School of Medicine（约翰霍普金斯大学医学院）；Washington University School of Medicine in St. Louis（圣路易斯华盛顿大学医学院）；University of Alabama at Birmingham Heersink School of Medicine（阿拉巴马大学伯明翰分校希尔斯金医学院）；Perelman School of Medicine at the University of Pennsylvania（宾夕法尼亚大学佩雷尔曼医学院）；New York University（纽约大学）
MaLei at MultiClinSUM: Summarisation of Clinical Documents using Perspective-Aware Iterative Self-Prompting with LLMs
University of Manchester, UK（曼彻斯特大学）；Modul University Vienna, Austria（维也纳Modul大学）；Leiden Institute of Advanced Computer Science (LIACS), Leiden University, The Netherlands（莱顿先进计算机科学研究所（LIACS）、莱顿大学）；Leiden University Medical Center, The Netherlands（莱顿大学医学中心）
InformGen: An AI Copilot for Accurate and Compliant Clinical Research Consent Document Generation
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of Edinburgh（爱丁堡大学）；Carle Illinois College of Medicine（卡尔伊利诺伊医学院）；Seoul National University Bundang Hospital（首尔大学盆唐医院）
Classifying Cancer Stage with Open-Source Clinical Large Language Models
1 College of Computing；Informatics Drexel University, Philadelphia PA, USA Email: cc3859,mml367；2 Department of Medical Oncology, Sidney Kimmel Cancer Center Thomas Jefferson University, Philadelphia, PA, USA Email
Clinical Document Metadata Extraction: A Scoping Review
University of Minnesota（明尼苏达大学）；Mayo Clinic（妙佑医疗国际）；University of Texas Health Science Center at Houston（德克萨斯大学休斯顿健康科学中心）；Oregon Health & Science University（俄勒冈健康与科学大学）
Coding-Free and Privacy-Preserving Agentic Framework for Data-Driven Clinical Research
Infmedix, Co., Ltd.（Infmedix公司）；Department of Transdisciplinary Studies, Seoul National University（首尔国立大学跨学科研究系）；Healthcare AI Research Institute, Seoul National University Hospital（首尔国立大学医院医疗人工智能研究所）；Department of Medicine, Seoul National University College of Medicine（首尔国立大学医学院医学系）；Department of Transdisciplinary Medicine, Seoul National University Hospital（首尔国立大学医院跨学科医学系）；Department of Radiology, Massachusetts General Hospital and Harvard Medical School（麻省总医院放射科及哈佛医学院）
Berta: an open-source, modular tool for AI-enabled clinical documentation
Department of Medicine, University of Alberta, Edmonton, Alberta, Canada（阿尔伯塔大学医学系，埃德蒙顿，阿尔伯塔，加拿大）；Department of Emergency Medicine, University of Alberta, Edmonton, Alberta, Canada（阿尔伯塔大学急诊医学系，埃德蒙顿，阿尔伯塔，加拿大）；Alberta Health Services, Edmonton, Alberta, Canada（阿尔伯塔省健康服务，埃德蒙顿，阿尔伯塔，加拿大）；Alberta Machine Intelligence Institute, Edmonton, Alberta, Canada（阿尔伯塔人工智能研究所，埃德蒙顿，阿尔伯塔，加拿大）；Department of Computer Science, University of Alberta, Edmonton, Alberta, Canada（阿尔伯塔大学计算机科学系，埃德蒙顿，阿尔伯塔，加拿大）
From Documents to Spans: Span-Centric Learning for LLM-based Explainable Medical Coding
School of Biomedical Engineering, Division of Life Sciences and Medicine, USTC（生物医学工程学院，生命科学与医学系，中国科学技术大学）；MIRACLE Center, Suzhou Institute for Advance Research, USTC（MIRACLE中心，苏州先进研究院，中国科学技术大学）；Jiangsu Provincial Key Laboratory of Multimodal Digital Twin Technology（江苏省多模态数字孪生技术重点实验室）；State Key Laboratory of Precision and Intelligent Chemistry, USTC（精密与智能化学国家重点实验室）
DENSE: Longitudinal Progress Note Generation with Temporal Modeling of Heterogeneous Clinical Notes Across Hospital Visits
Department of Computer Science and Information Systems, Birla Institute of Technology and Science, Pilani, Hyderabad Campus（计算机科学与信息系统系，比拉理工学院，比拉理工学院，海得拉巴校区）
Clinical Document Corpora -- Real Ones, Translated and Synthetic Substitutes, and Assorted Domain Proxies: A Survey of Diversity in Corpus Design, with Focus on German Text Data
Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig（莱比锡大学医学信息学、统计学与流行病学研究所）
LongHealth: A Question Answering Benchmark with Long Clinical Documents
Technical University of Munich（慕尼黑工业大学）；Charité – Universitätsmedizin Berlin（柏林夏里特医学院）；University Hospital Aachen（亚琛大学医院）；Kaduceo；Berliner Hochschule für Technik (BHT)（柏林工业大学）；Mass General Brigham, Harvard Medical School（麻省总医院布莱根医疗集团，哈佛医学院）；Maastricht University（马斯特里赫特大学）；University Hospital RWTH Aachen（亚琛工业大学医院）；Technical University Dresden（德累斯顿工业大学）；German Heart Center Munich（慕尼黑德国心脏中心）
Detecting automatically the layout of clinical documents to enhance the performances of downstream natural language processing
Sorbonne Université（索邦大学）；Inserm（法国国家健康与医学研究院）；Institut Pierre-Louis d'Epidémiologie et de Santé Publique（皮埃尔-路易流行病学与公共卫生研究所）；Assistance Publique-Hôpitaux de Paris（巴黎公共医疗集团）；LIMICS（医学信息学与信号处理实验室）
DART: A Structured Dataset of Regulatory Drug Documents in Italian for Clinical NLP
University of Naples Federico II, Department of Electrical Engineering（那不勒斯费德里科二世大学电气工程系）；Consorzio Interuniversitario Nazionale per l'Informatica (CINI) - ITEM National Lab, Complesso Universitario Monte S.Angelo, Naples, Italy（国家信息计算联合研究所（CINI）- ITEM国家实验室，那不勒斯意大利大学综合体）；Northwestern University, Department of Computer Science, McCormick School of Engineering（西北大学计算机科学系，麦科姆工程学院）
Auxiliary Knowledge-Induced Learning for Automatic Multi-Label Medical Document Classification
University of Western Ontario（西安大略大学）；Vector Institute for Artificial Intelligence（向量人工智能研究院）；Dalhousie University（达尔豪斯大学）；University of Toronto（多伦多大学）
Discharge Summary Hospital Course Summarisation of In Patient Electronic Health Record Text with Clinical Concept Guided Deep Pre-Trained Transformer Models
King’s College London（伦敦国王学院）；King’s College Hospital NHS Foundation Trust（国王学院医院NHS基金会信托）；University College London（伦敦大学学院）
Developing a general-purpose clinical language inference model from a large corpus of clinical notes
Bakar Computational Health Sciences Institute, University of California, San Francisco（加州大学旧金山分校巴卡尔计算健康科学研究所）；Center for Data-driven Insights and Innovation, University of California, Office of the President（加州大学校长办公室数据驱动洞察与创新中心）；University of California, San Francisco（加州大学旧金山分校）
