Understanding medication events in clinical narratives is essential to achieving a complete picture of a patient's medication history. While prior research has explored classification of medication changes from clinical notes, studies to date have not considered the necessary clinical context needed for their use in real-world applications, such as medication timeline generation and medication reconciliation. In this paper, we present the Contextualized Medication Event Dataset (CMED), a dataset for capturing relevant context of medication changes documented in clinical notes, which was developed using a novel conceptual framework that organizes context for clinical events into various orthogonal dimensions. In this process, we define specific contextual aspects pertinent to medication change events, characterize the dataset, and report the results of preliminary experiments. CMED consists of 9,013 medication mentions annotated over 500 clinical notes, and will be released to the community as a shared task in 2021.
Ensemble BERT for Medication Event Classification on Electronic Health Records (EHRs)
Center of Excellence in Research and Education for Big Military Data Intelligence (CREDIT Center)（大数据智能研究与教育中心）；Department of Electrical and Computer Engineering（电气与计算机工程系）；Prairie View A&M University（普拉姆维尤农业与机械大学）；Texas A&M University System（德克萨斯农工大学系统）
Assessment of Amazon Comprehend Medical: Medication Information Extraction
NYU Langone Health（纽约大学朗格尼医学中心）
2018年11月27日，Amazon Web Services（AWS）发布了Amazon Comprehend Medical（ACM），这是一个基于深度学习的系统，可以从临床文本笔记中自动提取临床概念（包括解剖结构、医疗状况、受保护的健康信息（PH）I、测试名称、治疗名称、医疗程序和药物）。对任何新数据产品的接受和信任都依赖于跨基准数据集和工具的独立验证，以建立和确认预期的结果质量。这项工作的重点是药物提取任务，特别是使用2009年i2b2药物提取挑战赛和2018年n2c2轨道2的官方测试集评估ACM：不良药物事件和EHR中的药物提取。总体而言，ACM的F评分为0.768和0.828。与各自挑战中的三个最佳系统相比，这些分数排名最低。为了进一步确定其药物提取性能的普遍性，这项工作还包括来自纽约大学Langone医学中心的一组随机内部临床文本注释。在这个语料库中，ACM获得了0.753的F分数。
Systematic Comparative Analysis of Large Pretrained Language Models on Contextualized Medication Event Extraction
Center of Excellence in Research and Education for Big Military Data Intelligence (CREDIT Center)（大数据智能卓越研究中心（CREDIT中心））；Department of Electrical and Computer Engineering（电气与计算机工程系）；Prairie View A&M University（普拉提维大学）；Texas A&M University System（德克萨斯A&M大学系统）
Learning the grammar of drug prescription: recurrent neural network grammars for medication information extraction in clinical texts
CHU Necker, AP-HP（巴黎公共医疗救助机构内克尔大学医院）；INSERM UMR-S 872（法国国家健康与医学研究院 UMR-S 872）；Sorbonne Paris Cité, Faculté de Médecine（索邦巴黎西岱大学医学院）；Université de Paris（巴黎大学）
Efficient extraction of medication information from clinical notes: an evaluation in two languages
University hospital of Strasbourg（斯特拉斯堡大学医院）；Inria（法国国家信息与自动化研究所）；Inserm（法国国家健康与医学研究院）；Université Paris Cité（巴黎西岱大学）；HeKA；Université Paris-Saclay（巴黎萨克雷大学）；CNRS（法国国家科学研究中心）；LISN（巴黎第十一大学计算机科学实验室）
Development and Testing of a Novel Large Language Model-Based Clinical Decision Support Systems for Medication Safety in 12 Clinical Specialties
Singapore General Hospital（新加坡中央医院）；Duke-NUS Medical School（杜克-新加坡国立大学医学院）；Singapore National Eye Centre（新加坡全国眼科中心）；Singapore Eye Research Institute（新加坡眼科研究所）；Singapore Health Services（新加坡保健服务）
PACE-RAG: Patient-Aware Contextual and Evidence-Constrained RAG for Clinical Drug Recommendation
Korea Advanced Institute of Science and Technology（韩国科学技术院）；Department of Neurology, Seoul National University Hospital（首尔国立大学医院神经科）；Asan Medical Center, University of Ulsan, College of Medicine（釜山大学医学院阿桑医院）；Haeundae Paik Hospital, Inje University（庆尚大学医院海undae医院）
InsightFlow: LLM-Driven Synthesis of Patient Narratives for Mental Health into Causal Models
Department of Mathematics, IIT Delhi（印度德里理工学院数学系）；Department of Electrical Engineering, IIT Delhi（印度德里理工学院电气工程系）；Department of Computer Science and Engineering, IIIT Manipur（曼尼普尔理工学院计算机科学与工程系）
Reliable Multilingual Orthopedic Decision Support from Clinical Narratives: Language-Aware Adaptation and Verification-Guided Deferral
School of Computer Science, Wuhan University（武汉大学计算机学院）；School of Software, Nanjing University of Information Science and Technology (NUIST)（南京信息工程大学软件学院）；Department of Orthopedic, Bahawal Victoria Hospital（巴哈瓦尔维多利亚医院骨科部门）
Identifying Symptoms of Delirium from Clinical Narratives Using Natural Language Processing
University of Florida（佛罗里达大学）；UF Health Shands Hospital（UF Health Shands医院）；University of California Los Angeles（加州大学洛杉矶分校）；UF Clinical and Translational Science Institute（UF临床与转化科学研究所）；North Florida/South Georgia Veterans Health Service（北佛罗里达/南乔治亚退伍军人卫生服务处）；College of Nursing, University of Florida（佛罗里达大学护理学院）；College of Public Health and Health Professions & College of Medicine, University of Florida（佛罗里达大学公共卫生与健康专业学院及医学院）
Lung Cancer Concept Annotation from Spanish Clinical Narratives
Centro de Tecnología Biomédica, Universidad Politécnica de Madrid（马德里理工大学生物医学技术中心）；Universidad Politécnica de Madrid（马德里理工大学）；ETS de Ingenieros Informáticos, Universidad Politécnica de Madrid（马德里理工大学计算机工程高等技术学院）
SemioLLM: Evaluating Large Language Models for Diagnostic Reasoning from Unstructured Clinical Narratives in Epilepsy
University of Tübingen（蒂宾根大学）；Technical University of Munich（慕尼黑工业大学）；University Clinic Tübingen（蒂宾根大学医院）；Hertie Institute for Clinical Brain Research（赫蒂临床脑研究所）；Excellence Cluster Machine Learning, Tübingen University（蒂宾根大学机器学习卓越集群）；Hertie Institute for AI in Brain Health (Hertie AI)（赫蒂人工智能脑健康研究所）
Detecting HIV-Related Stigma in Clinical Narratives Using Large Language Models
Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida（佛罗里达大学医学院健康结果与生物医学信息学系）；Department of Epidemiology, College of Public Health and Health Professions, University of Florida（佛罗里达大学公共卫生与健康专业学院流行病学系）；Preston A. Wells, Jr. Center for Brain Tumor Therapy, Lillian S. Wells Department of Neurosurgery, University of Florida（佛罗里达大学莉莉安·S·威尔斯神经外科系普雷斯顿·A·威尔斯脑肿瘤治疗中心）
