Predicting molecular subtype in breast cancer using deep learning on mammography images [0.03%]
基于乳腺X线摄影图像的深度学习预测乳腺癌分子亚型
Yunzhao Luo,Jing Wei,Yang Gu et al.
Yunzhao Luo et al.
Objectives: This study aimed to develop and evaluate a deep learning model for predicting molecular subtypes of breast cancer using conventional mammography images, offering a potential alternative to invasive diagnostic ...
Histopathological grading affects survival in patients with isocitrate dehydrogenase-wildtype gliomas [0.03%]
组织病理分级影响异柠檬酸脱氢酶野生型胶质瘤患者的生存率
Ziming Hou,Dongyuan Liu,Zhe Hou et al.
Ziming Hou et al.
Background: The World Health Organization (WHO) Classification of Tumors of the Central Nervous System (2021) defines lower-grade (WHO grade II/III) isocitrate dehydrogenase (IDH) wild-type astrocytoma as glioblastoma, ID...
Machine learning-based analysis identifies glucose metabolism-related genes ADPGK as potential diagnostic biomarkers for clear cell renal cell carcinoma [0.03%]
基于机器学习的分析识别出与葡萄糖代谢相关的基因ADPGK可能是透明细胞肾细胞癌潜在的诊断生物标志物
Tie Li,Shijin Wang,Guandu Li et al.
Tie Li et al.
Introduction: Clear cell renal cell carcinoma, with its high morbidity and mortality, is one of the more difficult diseases in the world and still lacks an effective therapeutic target. The primary way they break down glu...
The potential of antibody-drug conjugates in immunotherapy for non-small cell lung cancer: current progress and future [0.03%]
抗体药物偶联物在非小细胞肺癌免疫治疗中的潜力：目前的进展和未来展望
Hongyu Lin,Xinyu Ma,Xinhai Zhu et al.
Hongyu Lin et al.
Antibody-drug conjugates (ADCs) have gained significant attention as a promising therapeutic strategy for non-small cell lung cancer (NSCLC), combining the precision of monoclonal antibodies with the potent cytotoxic effects of chemotherapy...
Development and validation of a prostate cancer risk prediction model for the elevated PSA population [0.03%]
高PSA人群前列腺癌风险预测模型的研制与验证
Junhui Wu,Xiaodong Jin,Jiali Li et al.
Junhui Wu et al.
Introduction: To develop and validate a dynamic clinical prediction model integrating prostate-specific antigen (PSA) and peripheral blood biomarkers for distinguishing benign from malignant prostate diseases in patients ...
Advancing breast cancer relapse prediction with radiomics and neural networks: a clinically interpretable framework [0.03%]
基于影像组学和神经网络的乳腺癌复发预测研究：一种临床可解释框架
Adnan Khalid,Muhammad Mursil,Carlos López Pablo et al.
Adnan Khalid et al.
Early assessment of breast cancer relapse can significantly impact survival rates and overall oncological outcomes, highlighting the need to use sophisticated diagnostic strategies in clinical trials. This work utilizes clinically relevant ...
A synthetic cohort analysis of postoperative management of primary cardiac angiosarcoma and a case report [0.03%]
原发性心脏血管肉瘤术后管理的合成队列分析及1例报道
Ying Cai,Hang Yang,Dan Yuan et al.
Ying Cai et al.
Background: Primary cardiac angiosarcoma is a rare and aggressive malignancy originating from the endothelial lining of cardiac blood vessels. The prognosis remains extremely poor. The study was to evaluate postoperative ...
A comparison of trends in the incidence of non-alcoholic steatohepatitis-related liver cancer in the BRICS countries from 1990 to 2021, alongside projections for the next 15 years [0.03%]
1990年至2021年金砖国家非酒精性肝炎相关肝癌发病率趋势对比及未来15年的预测展望
Congjie Chen,Siying Huang,Huiqiang Wu et al.
Congjie Chen et al.
Background: Despite the ongoing rise in the global burden of non-alcoholic steatohepatitis-related liver cancer (NALC), systematic analyses and long-term trend projections of the disease's burden in the BRICS countries (B...
Xiaoyang Ma,Xiaolin Yu,Chuan Wu et al.
Xiaoyang Ma et al.
In tumors, extrachromosomal DNA (ecDNA) is an important driver of oncogene expression, genomic instability, the evolution of drug resistance, and poor patient prognosis. ecDNA is present in various tumors but is rarely found in normal cells...
Comparative analysis of machine learning techniques on the BraTS dataset for brain tumor classification [0.03%]
基于BraTS数据集的脑肿瘤分类机器学习算法比较分析研究
Shuping Wang,Min Li
Shuping Wang
Introduction: Accurate classification of brain tumors from MRI scans is a critical task for improving patient outcomes. Machine learning (ML) and deep learning (DL) methods have shown promise in this domain, but their rel...