Self-Supervised Transformer-Based Pipeline for Liver Tumor Segmentation and Type Classification [0.03%]
基于自监督Transformer的肝肿瘤分割与分类模型
Ramtin Mojtahedi,Mohammad Hamghalam,Jacob J Peoples et al.
Ramtin Mojtahedi et al.
Purpose: It is essential to detect and segment liver tumors to guide treatment and track disease progression. To reduce the need for large annotated data sets, we present an end-to-end pipeline that uses self-supervised p...
Novel R Shiny Tool for Survival Analysis With Time-Varying Covariate in Oncology Studies: Overcoming Biases and Enhancing Collaboration [0.03%]
一种新颖的R Shiny工具：用于肿瘤学研究中带有时变协变量的生存分析，克服偏差和增强协作
Yimei Li,Yang Qiao,Fei Gao et al.
Yimei Li et al.
Purpose: Our study is motivated by evaluating the role of hematopoietic cell transplantation (HCT) after chimeric antigen receptor T-cell (CAR-T) therapy for ALL, a debated topic. Because patients may receive HCT at diffe...
Simulation-Based Evaluation of a Large Language Model-Enabled Clinical Decision Support Platform in Oncology [0.03%]
基于模拟的大型语言模型驱动的肿瘤学临床决策支持平台评估
Nesrine Lajmi,Mehul Patel,Gareth Obery et al.
Nesrine Lajmi et al.
Purpose: A core clinical task is to synthesize fragmented patient data into a coherent summary to support decision making. However, electronic health record (EHR) inefficiencies burden clinicians and contribute to their c...
Improving Survival Models in Health Care by Balancing Imbalanced Cohorts: A Novel Approach [0.03%]
一种新颖的医疗保健生存模型改进方法：平衡不平衡群体
Catherine Ning,Dimitris Bertsimas,Per Eystein Lønning et al.
Catherine Ning et al.
Purpose: We explore whether survival model performance in underrepresented high- and low-risk subgroups-regions of the prognostic spectrum where clinical decisions are most consequential-can be improved through targeted r...
Causal Cascade of Symptoms on Patient Functioning and Health-Related Quality of Life in Non-Small Cell Lung Cancer and Metastatic Breast Cancer [0.03%]
非小细胞肺癌和转移性乳腺癌患者的症状连锁反应及其对患者功能状态和生活质量的影响
Donald E Stull
Donald E Stull
Purpose: Health-related quality of life (HRQoL) is a valuable counterpart to other end points in oncology trials. However, when analyzing the effect of treatment on HRQoL, results are often mixed. Cancer and its treatment...
Assessing the Detection Power of Genome-Wide Copy Number Variation Profiles in Prostate Cancer Using Simulated Shallow Whole-Genome Sequencing Data [0.03%]
利用模拟浅层全基因组测序数据评估前列腺癌中全基因组拷贝数变异谱系的检测能力
Samhita Pamidimarri Naga,Peter H J Slootbeek,Sofie H Tolmeijer et al.
Samhita Pamidimarri Naga et al.
Purpose: Shallow whole-genome sequencing (sWGS) is a cost-effective approach for detecting genome wide copy number profiles in tumor samples. In metastatic castration-resistant prostate cancer (mCRPC), recognizing homolog...
PREPARE ALL: An Artificial Intelligence Tool for Predicting Relapse in Children With Acute Lymphoblastic Leukemia [0.03%]
预测急性淋巴细胞白血病患儿复发的人工智能工具
Subikksha Saravanan,Raghunathan Rengaswamy,Gaurav Narula et al.
Subikksha Saravanan et al.
Purpose: The Pediatric Relapse Prediction and Risk Evaluation for Acute Lymphoblastic Leukemia (PREPARE-ALL) tool aims to predict relapse in pediatric ALL by integrating clinical expertise with artificial intelligence and...
Multicenter Study
JCO clinical cancer informatics. 2026 Jan:10:e2500222. DOI:10.1200/CCI-25-00222 2026
Impact of Real-World Response to First-Line Immunotherapy and Chemotherapy on Subsequent Treatment Outcomes in Patients With Advanced or Metastatic Non-Small Cell Lung Cancer [0.03%]
一线免疫治疗和化疗对晚期或转移性非小细胞肺癌患者后续治疗结局的现实世界响应影响分析
Jyoti Malhotra,Shilpa Viswanathan,Shivani K Mhatre et al.
Jyoti Malhotra et al.
Purpose: This study examined real-world overall survival (rwOS) in patients with advanced or metastatic non-small cell lung cancer (a/mNSCLC) treated with combination immunotherapy (IO) and platinum chemotherapy in first ...
Knowledge Representation of a Multicenter Adolescent and Young Adult Cancer Infrastructure: Development of the STRONG AYA Knowledge Graph [0.03%]
多中心青少年和年轻人癌症基础设施的知识表示：STRONG AYA知识图的开发
Joshi Hogenboom,Varsha Gouthamchand,Charlotte Cairns et al.
Joshi Hogenboom et al.
Purpose: Rare diseases are difficult to fully capture, and regularly call for large, geographically dispersed initiatives. Such initiatives are often met with data harmonization challenges. These challenges render data in...
Multicenter Study
JCO clinical cancer informatics. 2026 Jan:10:e2500177. DOI:10.1200/CCI-25-00177 2026
Time-Series Clustering Captures Patterns of Early Immune Effector Cell-Associated Hematotoxicity That Are Predictable Using Tree-Based Models [0.03%]
基于树的模型预测免疫效应细胞相关血液毒性的早期模式
Emily C Liang,Yein Jeon,Yang Qiao et al.
Emily C Liang et al.
Purpose: Immune effector cell-associated hematotoxicity (ICAHT) is a major cause of nonrelapse mortality after chimeric antigen receptor (CAR) T-cell therapy. We hypothesized that unsupervised time-series clustering could...