Pilot Testing of a Multicomponent Cancer Pain-Cognitive Behavioral Therapy mHealth App for Patients With Advanced Cancer [0.03%]
晚期癌症患者多组件癌症疼痛认知行为疗法移动健康应用程序的试点测试
Desiree R Azizoddin,Sara M DeForge,Jian Zhao et al.
Desiree R Azizoddin et al.
Purpose: Patients with advanced cancer often experience pain symptoms. Pain-cognitive behavioral therapy (pain-CBT) represents an effective psychological treatment for chronic pain, yet access remains limited. We conducte...
Review of Large Language Models for Patient and Caregiver Support in Cancer Care Delivery [0.03%]
癌症护理传递中患者和照顾者支持的大规模语言模型综述
Ramez Kouzy,Elaine E Cha,Allison Rosen et al.
Ramez Kouzy et al.
This narrative review examines the current landscape and evidence regarding large language model (LLM) applications designed to support patients with cancer and caregivers. We analyzed peer-reviewed literature, conference proceedings, and i...
Utilization of Lung Cancer Registries in Learning Health Systems for Health Care Improvement [0.03%]
肺癌登记在学习型卫生体系中对医疗卫生改善的应用研究
Rob G Stirling,David R Baldwin,David Heineman et al.
Rob G Stirling et al.
Purpose: Lung cancer is the leading global cause of cancer mortality with substantial evidence of inequity, disparity in process and outcomes, and unwarranted clinical variation. Over the last decades, there has been majo...
Leveraging the Rural-Urban Commuting Area Tool to Address Geographic Disparities in Cancer Care: A Dual-Application Framework for Institutional and National Initiatives [0.03%]
利用城乡通勤区工具解决癌症护理的地域差异：机构和国家倡议的双重应用框架
Meredith C B Adams,Cody L Hudson,Matthew L Perkins et al.
Meredith C B Adams et al.
Purpose: We developed and validated a dual-purpose, open-access Rural-Urban Commuting Area (RUCA) tool to standardize geographic coding for cancer disparities research, addressing National Institutes of Health (NIH) Helpi...
Development, External Validation, and Deployment of RFAN-ML: A Machine Learning Model to Estimate Renal Function After Nephrectomy [0.03%]
RFAN-ML模型的开发、外部验证和应用：一种估算肾切除术后肾功能的机器学习模型
Jesse Persily,Steven L Chang,Chen Chen et al.
Jesse Persily et al.
Purpose: Partial nephrectomy has been advocated as the preferred surgical approach for small kidney tumors over total nephrectomy. However, partial nephrectomy is associated with increased perioperative risk. Estimating r...
Longitudinal Synthetic Data Generation by Artificial Intelligence to Accelerate Clinical and Translational Research in Breast Cancer [0.03%]
人工智能纵向合成数据生成加速乳腺癌临床与转化研究
Elena Zazzetti,Saverio D&#x;Amico,Flavia Jacobs et al.
Elena Zazzetti et al.
Purpose: Real-world data (RWD) are critical for breast cancer (BC) research but are limited by privacy concerns, missing information, and data fragmentation. This study explores synthetic data (SD) generated through advan...
Reasoning Models for Text Mining in Oncology: A Comparison Between o1 Preview, GPT-4o, and GPT-5 at Different Reasoning Levels [0.03%]
肿瘤学文本挖掘的推理模型比较：在不同层次上比较o1 Preview、GPT-4o和GPT-5的能力
Paul Windisch,Fabio Dennstädt,Julia Weyrich et al.
Paul Windisch et al.
Purpose: Chain-of-thought prompting is a method to make large language models generate intermediate reasoning steps when solving a complex problem. OpenAI's o1 preview and GPT-5 have been trained to create such a chain of...
Comparative Study
JCO clinical cancer informatics. 2025 Nov:9:e2400311. DOI:10.1200/CCI-24-00311 2025
Augmenting Large Language Models With National Comprehensive Cancer Network Guidelines for Improved and Standardized Adjuvant Therapy Recommendations in Postoperative Breast Cancer Cases [0.03%]
利用国家综合癌症网络指南增强大型语言模型以改善和标准化乳腺癌术后辅助治疗建议
Serene Si Ning Goh,Ragunathan Mariappan,Grace Soo Woon Tan et al.
Serene Si Ning Goh et al.
Purpose: Multidisciplinary breast tumor boards (MTBs) are essential for optimizing breast cancer treatment but face challenges related to logistics, variability in expertise, and lack of standardization. Large language mo...
Artificial Intelligence System for Psychospiritual Distress in Family Caregivers of Patients With Terminal Cancer: A Retrospective Study [0.03%]
晚期癌症患者家庭照顾者的心理精神困扰人工智能系统：一项回顾性研究
Kento Masukawa,Ryusho Suzuki,Momoka Tanno et al.
Kento Masukawa et al.
Purpose: Family caregivers of patients with terminal cancer need psychospiritual care. The assessment of their psychospiritual distress is challenging. An automated system can be used to detect psychospiritual distress fr...
Integrating a Shareable Artificial Intelligence Model Into Clinical Research for Cancer Recurrence in Patients With Breast and Colorectal Cancer [0.03%]
将共享型人工智能模型整合应用于乳腺癌和结直肠癌患者癌症复发的临床研究
Anlan Cao,Kristina L Johnson,Ijeamaka Anyene Fumagalli et al.
Anlan Cao et al.
Purpose: Cancer recurrence in clinical settings is documented in unstructured text, requiring labor-intensive manual record review to extract this outcome. A shareable natural language processing model developed at Dana-F...