MedDec: A Dataset for Extracting Medical Decisions from Discharge Summaries
Miner School of Computer & Information Sciences, University of Massachusetts Lowell（马萨诸塞大学洛厄尔分校 Miner 计算机与信息科学学院）；Institute for Medical Engineering and Science, Massachusetts Institute of Technology（麻省理工学院医学工程与科学研究院）
Mohamed Elgaar, Jiali Cheng, Nidhi Vakil, Hadi Amiri, Leo Anthony Celi
Medical decisions directly impact individuals' health and well-being. Extracting decision spans from clinical notes plays a crucial role in understanding medical decision-making processes. In this paper, we develop a new dataset called "MedDec", which contains clinical notes of eleven different phenotypes (diseases) annotated by ten types of medical decisions. We introduce the task of medical decision extraction, aiming to jointly extract and classify different types of medical decisions within clinical notes. We provide a comprehensive analysis of the dataset, develop a span detection model as a baseline for this task, evaluate recent span detection approaches, and employ a few metrics to measure the complexity of data samples. Our findings shed light on the complexities inherent in clinical decision extraction and enable future work in this area of research. The dataset and code are available through https://github.com/CLU-UML/MedDec.
MeDiSumQA: Patient-Oriented Question-Answer Generation from Discharge Letters
Institute for AI in Medicine (IKIM), University Hospital Essen（埃森大学医院人工智能医学研究所（IKIM））；NVIDIA（英伟达公司）；Cancer Research Center Cologne Essen (CCCE), University Medicine Essen（埃森大学医学院科隆埃森癌症研究中心（CCCE））；German Cancer Consortium (DKTK, Partner site Essen)（德国癌症联盟（DKTK，埃森合作站点））；TU Dortmund（多特蒙德工业大学）
A Corpus for Detecting High-Context Medical Conditions in Intensive Care Patient Notes Focusing on Frequently Readmitted Patients
Massachusetts Institute of Technology（麻省理工学院）；University of Massachusetts（马萨诸塞大学）；Harvard T.H. Chan School of Public Health（哈佛大学陈曾熙公共卫生学院）；Massachusetts General Hospital（麻省总医院）；Tufts University School of Medicine（塔夫茨大学医学院）；Beth Israel Deaconess Medical Center（贝斯以色列女执事医疗中心）；Washington University School of Medicine（华盛顿大学医学院）；Philips Research North America（飞利浦北美研究院）；Harvard University（哈佛大学）；Adobe Research（Adobe研究院）
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）
Phase 1 Implementation of LLM-generated Discharge Summaries showing high Adoption in a Dutch Academic Hospital
Department of Health Information Office, Data & Digitalization, University Medical Center（健康信息办公室、数据与数字化化大学医院）；Department of Trauma Surgery / Orthopedics, University Medical Center（创伤外科/骨科大学医院）；Department of Orthopaedic Surgery, Massachusetts General Hospital（骨科手术科马萨诸塞总医院）；Harvard Medical School Orthopaedic Trauma Initiative（哈佛医学院骨创伤倡议）；Department of Orthopaedic Surgery and Sports Medicine, Amsterdam UMC location University of Amsterdam（骨科手术与运动医学部门，阿姆斯特丹UMC地点大学）；Department of Orthopaedic Trauma, Flinders University Medical Centre（骨创伤部门，弗林德斯大学医疗中心）；Department of Otolaryngology – Head and Neck Surgery, University Medical Center（耳鼻喉科-头颈外科大学医院）；Department of Pediatrics, Pediatrics Nephrology, Beatrix Children’s Hospital, University Medical Center（儿科、儿科肾病学，比西特儿童医院，大学医院）
De-identifying Australian Hospital Discharge Summaries: An End-to-End Framework using Ensemble of Deep Learning Models
University of New South Wales（新南威尔士大学）；The Australian e-Health Research Centre, CSIRO（澳大利亚联邦科学与工业研究组织澳大利亚电子健康研究中心）；Australian Institute of Health and Welfare（澳大利亚卫生与福利研究所）
EHRNote-ChatQA: A Benchmark for Evidence-Grounded Multi-Turn Clinical Question Answering over Longitudinal Discharge Summaries
KAIST（韩国科学技术院）；Seoul National University（首尔大学）；Seoul National University Bundang Hospital（首尔大学盆唐医院）；SAIHST, Sungkyunkwan University（成均馆大学）；Yonsei University College of Medicine（延世大学医学院）；Gangnam Severance Hospital（江南塞弗伦斯医院）；Severance Hospital（塞弗伦斯医院）；Seoul Medical Center（首尔医疗中心）；Seoul National University Hospital（首尔大学医院）；National Cancer Center（国立癌症中心）；Icahn School of Medicine at Mount Sinai（西奈山伊坎医学院）；Samsung Medical Center（三星医疗中心）
GNTeam at 2018 n2c2: Feature-augmented BiLSTM-CRF for drug-related entity recognition in hospital discharge summaries
School of Computer Science, The University of Manchester（曼彻斯特大学计算机学院）；Health eResearch Center, The University of Manchester（曼彻斯特大学健康电子研究中心）；The Alan Turing Institute（艾伦·图灵研究所）
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）
Exploring Optimal Granularity for Extractive Summarization of Unstructured Health Records: Analysis of the Largest Multi-Institutional Archive of Health Records in Japan
Tokyo Metropolitan University（东京都立大学）；RIKEN（理化学研究所）；National Hospital Organization（国立医院机构）；Kitami Institute of Technology（北见工业大学）
MedFactEval and MedAgentBrief: A Framework and Workflow for Generating and Evaluating Factual Clinical Summaries
Center for Biomedical Informatics Research, Stanford University（生物医学信息学研究所在斯坦福大学）；Department of Biomedical Data Science, Stanford University（生物医学数据科学系，斯坦福大学）；Stanford Health Care（斯坦福健康中心）；Department of Anesthesiology and Pain Medicine, Stanford Medicine（麻醉与疼痛医学系，斯坦福医学院）；Department of Radiology, Stanford University（放射科，斯坦福大学）；Stanford Clinical Excellence Research Center, Stanford University（斯坦福临床卓越研究中心，斯坦福大学）；Department of Medicine, Stanford University（医学系，斯坦福大学）
MIT（麻省理工学院）；MIT-IBM Watson AI Lab（麻省理工学院-IBM沃森人工智能实验室）；University of Massachusetts Lowell（马萨诸塞大学洛厄尔分校）；IBM Research（IBM研究院）；Fidelity Investments（富达投资）；Beth Israel Deaconess Medical Center（贝斯以色列女执事医疗中心）；University of the Philippines（菲律宾大学）；Northeastern University（东北大学）
Ontology-Driven and Weakly Supervised Rare Disease Identification from Clinical Notes
University of Edinburgh（爱丁堡大学）；Health Data Research UK（英国健康数据研究所）；University of Oxford（牛津大学）；University College London（伦敦大学学院）；The University of Manchester（曼彻斯特大学）
Clinical Term Extraction using Open-Source Small Language Models
Informatics and Data Science Institute（信息学与数据科学研究所）；Biomedical Informatics, Biostatistics and Medical Epidemiology Department（生物医学信息学、生物统计学与医学流行病学系）；Department of Occupational Therapy（职业治疗系）；University of Missouri, Columbia, Missouri, USA（密苏里大学哥伦比亚分校）
