Large Language Model-Based Classification of Case Report Abstracts: A Pilot Study on Interactions Between Radiotherapy and Systemic Therapies [0.03%]
基于大型语言模型的病例报告摘要分类：放射治疗与系统治疗相互作用的试点研究
Fabio Dennstädt,Til Bobnar,Alin Handra et al.
Fabio Dennstädt et al.
Purpose: The growing volume of biomedical literature, especially in oncology, necessitates automated tools for extracting clinically relevant information. Large language models (LLMs) offer promising capabilities for data...
Estimating Small Area Statistics and Developing a Novel Mapping Tool to Display Them Using a User-Centered Design Process [0.03%]
基于以用户为中心的设计过程的小区域统计量估计及新型地图绘制工具开发
Erin O Wissler Gerdes,Jinyi Cai,Carly Mahoney et al.
Erin O Wissler Gerdes et al.
Purpose: Cancer registries are often asked to present cancer data for small geographic areas to inform and facilitate targeted interventions and prevention programs. However, it is challenging to compute and visualize rel...
Knowledge and Use of Artificial Intelligence Among Oncology Faculty and Trainees at a Comprehensive Cancer Center in 2025 [0.03%]
2025年综合性癌症中心肿瘤学教职员工和受训人员的人工智能知识和使用情况
Keri Schadler,Ann Klopp,Ramez Kouzy et al.
Keri Schadler et al.
Purpose: Artificial intelligence (AI) has been used in medicine for decades, but recent advances in machine learning and large language models have rapidly expanded its accessibility and applications in oncology. Although...
Machine Learning Risk Stratification Approach Using Patient-Reported Outcomes for Forecasting Unplanned Health Care Use and Symptom Burden in Cancer Survivors [0.03%]
Akina Natori,Jerry R Bonnell,Vasileios Stathias et al.
Akina Natori et al.
Purpose: Effective risk stratification in cancer survivorship requires handling longitudinal data characterized by multimodal inputs, irregular follow-up, and recurrent clinical events. This study evaluated the incrementa...
Machine Learning Model Predicts Monoclonal Gammopathy Using Routine Laboratory Values [0.03%]
基于常规检验值预测单克隆丙球蛋白血症的机器学习模型
Mercedeh Movassagh,Cihan Kaya,Con Skordis et al.
Mercedeh Movassagh et al.
Purpose: Monoclonal gammopathy (MG) is a disorder defined by the presence of monoclonal immunoglobulin. Monoclonal protein (M-protein) serves as an important biomarker for the spectrum of MG that includes plasma cell myel...
Interactive Medication Calendars to Support At-Home Care of Pediatric Patients With ALL [0.03%]
互动的药物日历在儿童急性淋巴细胞白血病居家护理中的应用
Lydia Haupt Levy,Clara C Hatch,Rachel Selig et al.
Lydia Haupt Levy et al.
Purpose: Pediatric ALL, the most common childhood cancer, requires complex, multiyear treatment. Most treatment occurs in the outpatient setting, and families must manage and administer chemotherapy and supportive care me...
User-Centered Development of the MyCare2 Comprehensive Digital Support Platform for Caregivers of Individuals With Cancer [0.03%]
以用户为中心的MyCare2综合数字支持平台的开发——用于癌症患者照护者的数字支持平台研究
Rachel A Pozzar,Tamryn F Gray,Manan M Nayak et al.
Rachel A Pozzar et al.
Purpose: Caregivers of adults with cancer face significant emotional and practical challenges. Digital tools may enhance caregiver preparedness and self-efficacy; however, few are developed through rigorous, user-centered...
Simulating Cancer Recurrence Patterns From Post-Treatment Viable Tumor Burden Distributions [0.03%]
基于治疗后肿瘤负荷分布的癌症复发模式仿真
Mohammad U Zahid,Joseph D Butner,David M Swanson et al.
Mohammad U Zahid et al.
Purpose: Ordinary differential equation mathematical models of tumor volume dynamics can accurately describe tumor growth and treatment response. Here, we extend such continuous models to also simulate outcomes. We concep...
Johnie Rose,Akhil Sarangadharan GeethaKumari,Siran M Koroukian et al.
Johnie Rose et al.
Purpose: Cancer registry data represent an indispensable tool for researchers and community outreach and engagement (COE) professionals seeking to understand and mitigate cancer burden in cancer center catchment areas and...
Interpreting Treatment Effects Using Posterior Probabilities: A Bayesian Reanalysis of 230 Phase III Oncology Trials [0.03%]
基于后验概率解释处理效果的一种贝叶斯再分析方法——对230项III期肿瘤学试验的再分析研究
Alexander D Sherry,Pavlos Msaouel,Gabrielle S Kupferman et al.
Alexander D Sherry et al.
Purpose: Most oncology trials define superiority according to dichotomized P value thresholds, which are frequently misinterpreted. Posterior probability, however, directly estimates the probability of the hypothesis at h...