Novel Electronic Health Record-Based Data Commons for Pancreatic Cancer [0.03%]
一种新型的基于电子健康记录的胰腺癌数据公共池
Kaleem S Ahmed,Clayton T Marcinak,Muhammad Maisam Ali et al.
Kaleem S Ahmed et al.
Purpose: Clinical research in pancreatic cancer (PC) has been limited because of a lack of granular data in national data sets. An electronic health record (EHR)-based data set specifically designed for PC has immense pot...
Clinical Trial Patient Matching: A Real-Time, Common Data Model and Artificial Intelligence-Driven System for Semiautomated Patient Prescreening in Cancer Clinical Trials [0.03%]
临床试验患者匹配：实时通用数据模型和人工智能驱动的系统在癌症临床试验中的半自动患者预筛选中的应用
Guannan Gong,Jessica Liu,Sameer Pandya et al.
Guannan Gong et al.
Purpose: Cancer clinical trial enrollment remains critically low at 5%-7% of adult patients despite exponential growth in available trials. Manual patient-trial matching represents a fundamental bottleneck, whereas curren...
ClinBioNGS: A Clinical Bioinformatics Pipeline for Integrated Analysis of Somatic Next-Generation Sequencing Cancer Panels [0.03%]
ClinBioNGS：一个用于综合分析体细胞下一代测序癌症基因组的临床 bioinformatics 管道
Raúl Marín,Ania Alay,Maria Ajenjo-Bauza et al.
Raúl Marín et al.
Purpose: Somatic next-generation sequencing (NGS) panels are widely used in precision oncology to detect clinically actionable genomic alterations. However, interpreting diverse DNA and RNA alterations remains challenging...
Extraction of Treatments and Responses From Non-Small Cell Lung Cancer Clinical Notes Using Natural Language Processing [0.03%]
基于自然语言处理技术的非小细胞肺癌临床文本中药物及反应信息抽取
Sonish Sivarajkumar,Subhash Edupuganti,David Lazris et al.
Sonish Sivarajkumar et al.
Purpose: Manual extraction of treatment outcomes from unstructured oncology clinical notes is a significant challenge for real-world evidence (RWE) generation. This study aimed to develop and evaluate a robust natural lan...
Tumor Board-Inspired Multiagent Artificial Intelligence System for Interpreting Oncology Guidelines [0.03%]
基于肿瘤委员会的多智能体人工智能系统解读肿瘤学指南
Jiasheng Wang,Kirti Arora,David M Swoboda et al.
Jiasheng Wang et al.
Purpose: Clinical guidelines are essential for evidence-based oncology care but are often long, complex, and difficult to navigate. We developed a multiagent artificial intelligence (AI) system to accurately retrieve and ...
Generative Artificial Intelligence Successfully Automates Data Extraction From Unstructured Magnetic Resonance Imaging Reports: Feasibility in Prostate Cancer Care [0.03%]
生成式人工智能成功地自动从非结构化磁共振成像报告中提取数据：前列腺癌治疗中的可行性研究
Anobel Y Odisho,Andrew W Liu,William A Pace et al.
Anobel Y Odisho et al.
Purpose: Radiology reports are stored as plain text in most electronic health records, rendering the data computationally inaccessible. Large language models are powerful tools for analyzing unstructured text but relative...
Synoptic Multidisciplinary Team Meeting Workflows to Promote Guideline-Based Classification of Resectability in Pancreatic Cancer: A Multicenter Prospective Study [0.03%]
基于指南的胰腺癌切除性分类综合多学科团队会议工作流程的多中心前瞻性研究
William McGahan,Nick Butler,Thomas O&#x;Rourke et al.
William McGahan et al.
Purpose: To address incomplete and inconsistent classification of pancreatic cancer resectability according to International Association of Pancreatology (IAP) anatomic, biologic, and conditional criteria. ...
Multicenter Study
JCO clinical cancer informatics. 2026 Jan:10:e2500255. DOI:10.1200/CCI-25-00255 2026
Artificial Intelligence-Assisted Error Detection in Complex Clinical Documentation: Leveraging Large Language Models to Enhance Patient Safety in Oncology [0.03%]
基于大型语言模型的复杂临床文档错误检测：利用人工智能提高肿瘤学患者安全性的辅助方法
Peter May,Sina Nokodian,Christoph Nuernbergk et al.
Peter May et al.
Purpose: In high-risk specialties such as oncology, errors in clinical documentation can have severe consequences, highlighting a need for enhanced safety checks. We therefore aimed to evaluate the capability of frontier ...
Dynamic Mortality Risk Prediction in Myelodysplastic Syndromes Using Longitudinal Clinical Data [0.03%]
基于纵向临床数据的动态预测骨髓衰竭性疾病患者病死率的研究
Jonathan Bobak,Philipp Spohr,Sarah Richter et al.
Jonathan Bobak et al.
Purpose: Patients with myelodysplastic syndromes (MDS) exhibit diverse disease trajectories necessitating different clinical approaches ranging from watch-and-wait strategies to hematopoietic stem cell transplantation. Ex...
Geospatial Analysis of Commission on Cancer-Accredited Centers Within Cancer Care Utilization-Based Catchment Areas [0.03%]
基于癌症护理利用的供血区内美国肿瘤委员会认证中心的空间分布分析
Nicole Rademacher,Connor Sisk,Joshua S Richman et al.
Nicole Rademacher et al.
Purpose: The Commission on Cancer (CoC) seeks to expand access to high-quality care through community engagement standards targeting centers' catchment areas and efforts to accredit centers in more areas including rural h...