Breakthroughs in malignancy therapy: New advances and emerging trends in renal cell carcinoma [0.03%]
恶性肿瘤治疗的突破：肾细胞癌的新进展和新兴趋势
Xieqiao Yan,Xiaowen Wu,Xinan Sheng
Xieqiao Yan
Immune decoding from a multi-omics perspective: Redefining pancreatic cancer tumor microenvironment [0.03%]
从多组学角度解码免疫特征：重新定义胰腺癌肿瘤微环境
Enkui Zhang,Yinmo Yang
Enkui Zhang
Xian Zhong,Jinyi Chen,Yan Zhang et al.
Xian Zhong et al.
Breakthroughs of chimeric antigen receptor T-cell therapy in hematological malignancies: From ex vivo to in vivo [0.03%]
嵌合抗原受体T细胞治疗血液系统恶性肿瘤的体内到体外突破性进展
Xuying Pei,Yuxuan Du,Meng Lyu et al.
Xuying Pei et al.
Updates of CSCO guidelines for diagnosis and treatment of lymphoma: 2026 edition [0.03%]
中国淋巴瘤诊断治疗指南更新（2026年版）
Weiping Liu,Donglu Zhao,Jun Ma et al.
Weiping Liu et al.
Rethinking false-negative rate of sentinel node navigation surgery after non-curative endoscopic submucosal dissection: Insights from SENORITA 2 trial [0.03%]
SENTINA研究后非治愈性ESD的哨点淋巴结阴性率再思考：SENORITA 2试验见解
Zimeng Wang,Zhi Zheng,Jie Yin et al.
Zimeng Wang et al.
Current trends and future directions of artificial intelligence in lung cancer diagnosis [0.03%]
人工智能在肺癌诊断中的现状、趋势和展望
Weilong Hu,Gang Wang,Li Ren et al.
Weilong Hu et al.
Lung cancer is the most lethal malignancy worldwide, largely due to its late detection after its progression to advanced stages. Over the last decade, artificial intelligence (AI) applications have shown significant potential in transformin...
From spatial maps to therapeutic targets: Next challenge for artificial intelligence in cancer spatial omics [0.03%]
从空间图谱到治疗靶点：人工智能在癌症空间组学中的下一个挑战
Hui Xu,Yuyuan Zhang,Yuqing Ren et al.
Hui Xu et al.
Revisiting nature of stage III non-small cell lung cancer: Anatomically defined, biologically systemic [0.03%]
重新审视III期非小细胞肺癌的性质：解剖学定义，生物学系统性
Guoyin Li,Xi Zhang,Xiaolu Fu et al.
Guoyin Li et al.
Stage III non-small cell lung cancer (NSCLC) is traditionally viewed as a locally advanced disease based on anatomic imaging. It is increasingly recognized as a systemic illness with localized manifestations, as evidenced by high rates of d...
CARE framework: Rethinking randomized controlled trials for medical artificial intelligence [0.03%]
医学人工智能的随机对照试验重构及 CARE 框架
Sicheng Yang,Qiuxia Yang,Yize Mao et al.
Sicheng Yang et al.