Harnessing Natural Language Processing to Assess Quality of End-of-Life Care for Children With Cancer [0.03%]
利用自然语言处理评估儿童癌症终末期护理的质量
Meghan E Lindsay,Sophia de Oliveira,Kate Sciacca et al.
Meghan E Lindsay et al.
Purpose: Data on end-of-life care (EOLC) quality, assessed through evidence-based quality measures (QMs), are difficult to obtain. Natural language processing (NLP) enables efficient quality measurement and is not yet use...
Kendall J Kiser,Michael Waters,Jocelyn Reckford et al.
Kendall J Kiser et al.
Purpose: Large language model (LLM) artificial intelligences may help physicians appeal insurer denials of prescribed medical services, a task that delays patient care and contributes to burnout. We evaluated LLM performa...
Validation of Non-Small Cell Lung Cancer Clinical Insights Using a Generalized Oncology Natural Language Processing Model [0.03%]
基于通用肿瘤自然语言处理模型的非小细胞肺癌临床研究验证
Rachel C Kenney,Xiaoren Chen,Kazuki Shintani et al.
Rachel C Kenney et al.
Purpose: Limited studies have used natural language processing (NLP) in the context of non-small cell lung cancer (NSCLC). This study aimed to validate the application of an NLP model to an NSCLC cohort by extracting NSCL...
Increasing Power in Phase III Oncology Trials With Multivariable Regression: An Empirical Assessment of 535 Primary End Point Analyses [0.03%]
基于多元回归提高III期肿瘤临床试验功效的实证评估——535个主要研究终点分析结果
Alexander D Sherry,Adina H Passy,Zachary R McCaw et al.
Alexander D Sherry et al.
Purpose: A previous study demonstrated that power against the (unobserved) true effect for the primary end point (PEP) of most phase III oncology trials is low, suggesting an increased risk of false-negative findings in t...
Machine Learning-Based Prediction of 1-Year Survival Using Subjective and Objective Parameters in Patients With Cancer [0.03%]
基于机器学习的预测癌症患者的主观和客观参数的一年生存率预测
Maria Rosa Salvador Comino,Paul Youssef,Anna Heinzelmann et al.
Maria Rosa Salvador Comino et al.
Purpose: Palliative care is recommended for patients with cancer with a life expectancy of
Response to Kempf et al on Methodological and Practical Aspects of a Distant Metastasis Detection Model [0.03%]
对Kempf等人关于远处转移检测模型的方法学和实践方面评论的回应
Ricardo Ahumada,Jocelyn Dunstan,Inti Paredes et al.
Ricardo Ahumada et al.
The More, the Better? Modalities of Metastatic Status Extraction on Free Medical Reports Based on Natural Language Processing [0.03%]
越多越好？基于自然语言处理的自由医疗报告转移状态提取模态研究
Emmanuelle Kempf,Sonia Priou,Ariel Cohen et al.
Emmanuelle Kempf et al.
Application of a Data Quality Framework to Ductal Carcinoma In Situ Using Electronic Health Record Data From the All of Us Research Program [0.03%]
适用性研究：使用“全民健康计划”的电子健康记录数据对导管原位癌进行数据质量框架分析
Lew Berman,Yechiam Ostchega,John Giannini et al.
Lew Berman et al.
Purpose: The specific aims of this paper are to (1) develop and operationalize an electronic health record (EHR) data quality framework, (2) apply the dimensions of the framework to the phenotype and treatment pathways of...
Automated Extraction of Patient-Centered Outcomes After Breast Cancer Treatment: An Open-Source Large Language Model-Based Toolkit [0.03%]
基于开源大型语言模型的乳腺癌治疗后患者结局自动化提取工具包
Man Luo,Shubham Trivedi,Allison W Kurian et al.
Man Luo et al.
Purpose: Patient-centered outcomes (PCOs) are pivotal in cancer treatment, as they directly reflect patients' quality of life. Although multiple studies suggest that factors affecting breast cancer-related morbidity and s...
Prostate-Specific Antigen Screening and Prostate Cancer Mortality: An Emulation of Target Trials in US Medicare [0.03%]
基于美国老年人医疗补助计划数据的前列腺特异性抗原筛查与前列腺癌死亡风险的队列研究模拟试验
Xabier García-Albéniz,John Hsu,Ruth Etzioni et al.
Xabier García-Albéniz et al.
Purpose: No consensus about the effectiveness of prostate-specific antigen (PSA) screening exists among clinical guidelines, especially for the elderly. Randomized trials of PSA screening have yielded different results, p...