Large Language Models as Decision-Making Tools in Oncology: Comparing Artificial Intelligence Suggestions and Expert Recommendations [0.03%]
大型语言模型作为肿瘤学决策工具：比较人工智能建议和专家推荐
Loic Ah-Thiane,Pierre-Etienne Heudel,Mario Campone et al.
Loic Ah-Thiane et al.
Purpose: To determine the accuracy of large language models (LLMs) in generating appropriate treatment options for patients with early breast cancer on the basis of their medical records. ...
Comparative Study
JCO clinical cancer informatics. 2025 Mar:9:e2400230. DOI:10.1200/CCI-24-00230 2025
Predictive Model of Acute Rectal Toxicity in Prostate Cancer Treated With Radiotherapy [0.03%]
放射治疗前列腺癌的急性直肠毒性预测模型
Keyur D Shah,Beow Y Yeap,Hoyeon Lee et al.
Keyur D Shah et al.
Purpose: To aid personalized treatment selection, we developed a predictive model for acute rectal toxicity in patients with prostate cancer undergoing radiotherapy with photons and protons. ...
Multicenter Study
JCO clinical cancer informatics. 2025 Mar:9:e2400252. DOI:10.1200/CCI-24-00252 2025
PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology [0.03%]
PLSKB:一个基于精准肿瘤学的互动知识系统，用于林奇综合症的诊断，治疗和筛查支持系统
Mahsa Dehghani Soufi,Reza Shirkoohi,Zohreh Sanaat et al.
Mahsa Dehghani Soufi et al.
Purpose: Understanding the genetic heterogeneity of Lynch syndrome (LS) cancers has led to significant scientific advancements. However, these findings are widely dispersed across various resources, making it difficult fo...
Novel Computational Pipeline Enables Reliable Diagnosis of Inverted Urothelial Papilloma and Distinguishes It From Urothelial Carcinoma [0.03%]
新型计算流程能准确诊断倒置尿路上皮乳头状瘤并将其与尿路上皮癌区分
Wei Shao,Michael Cheng,Antonio Lopez-Beltran et al.
Wei Shao et al.
Purpose: With the aid of ever-increasing computing resources, many deep learning algorithms have been proposed to aid in diagnostic workup for clinicians. However, existing studies usually selected informative patches fro...
Virtual Health Care Encounters for Lung Cancer Screening in a Safety-Net Population: Observations From the COVID-19 Pandemic [0.03%]
在安全网人群中进行肺癌筛查的虚拟医疗会面：“COVID-19”流行病中的观察
Mary E Gwin,Urooj Wahid,Sheena Bhalla et al.
Mary E Gwin et al.
Purpose: The COVID-19 pandemic disrupted normal mechanisms of health care delivery and facilitated the rapid and widespread implementation of telehealth technology. As a result, the effectiveness of virtual health care vi...
Early Circulating Tumor DNA Kinetics as a Dynamic Biomarker of Cancer Treatment Response [0.03%]
早期循环肿瘤DNA动力学作为癌症治疗反应的动态生物标志物
Aaron Li,Emil Lou,Kevin Leder et al.
Aaron Li et al.
Purpose: Circulating tumor DNA (ctDNA) assays are promising tools for the prediction of cancer treatment response. Here, we build a framework for the design of ctDNA biomarkers of therapy response that incorporate variati...
Preoperative Maximum Standardized Uptake Value Emphasized in Explainable Machine Learning Model for Predicting the Risk of Recurrence in Resected Non-Small Cell Lung Cancer [0.03%]
可解释机器学习模型在预测切除的非小细胞肺癌复发风险中强调的最大标准化摄取值
Takafumi Iguchi,Kensuke Kojima,Daiki Hayashi et al.
Takafumi Iguchi et al.
Purpose: To comprehensively analyze the association between preoperative maximum standardized uptake value (SUVmax) on 18F-fluorodeoxyglucose positron emission tomography-computed tomography and postoperative recurrence i...
Erratum: Real-World Outcomes in Patients With Metastatic Renal Cell Carcinoma Treated With First-Line Nivolumab Plus Ipilimumab in the United States [0.03%]
错误！：接受尼伏鲁单抗 plus 依匹鲁单抗一线治疗的美国转移性肾细胞癌患者的现实世界结果
Gurjyot K Doshi,Andrew J Osterland,Ping Shi et al.
Gurjyot K Doshi et al.
Published Erratum
JCO clinical cancer informatics. 2025 Mar:9:e2500026. DOI:10.1200/CCI-25-00026 2025
Using a Longformer Large Language Model for Segmenting Unstructured Cancer Pathology Reports [0.03%]
使用Longformer大型语言模型对非结构化癌症病理报告进行分段
Damien Fung,Gregory Arbour,Krisha Malik et al.
Damien Fung et al.
Purpose: Many Natural Language Processing (NLP) methods achieve greater performance when the input text is preprocessed to remove extraneous or unnecessary text. A technique known as text segmentation can facilitate this ...
Prospective Clinical Implementation of Paige Prostate Detect Artificial Intelligence Assistance in the Detection of Prostate Cancer in Prostate Biopsies: CONFIDENT P Trial Implementation of Artificial Intelligence Assistance in Prostate Cancer Detection [0.03%]
PAIGE前列腺检测人工智能在前列腺活检中协助前列腺癌检测的临床应用展望：CONFIDENT P试验中的人工智能辅助前列腺癌检测的应用
Rachel N Flach,Carmen van Dooijeweert,Tri Q Nguyen et al.
Rachel N Flach et al.
Purpose: Pathologists diagnose prostate cancer (PCa) on hematoxylin and eosin (HE)-stained sections of prostate needle biopsies (PBx). Some laboratories use costly immunohistochemistry (IHC) for all cases to optimize work...
Clinical Trial
JCO clinical cancer informatics. 2025 Mar:9:e2400193. DOI:10.1200/CCI-24-00193 2025