日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Exploring the association between complete blood cell count-derived inflammatory biomarkers and cancer incidence through interpretable machine learning models: A study based on NHANES 1999 to 2016

利用可解释的机器学习模型探索全血细胞计数衍生的炎症生物标志物与癌症发病率之间的关联:一项基于1999年至2016年NHANES数据的研究

Zhao, Sijun; Fu, Ping; Lin, Liangqing; Zhou, Hui; Huang, Yunjun; Li, Yang; Tang, Chunyan

Management of infection and ocular complications in pediatric SJS/TEN-like acute graft-versus-host disease: a clinical case study and literature review

儿童SJS/TEN样急性移植物抗宿主病感染及眼部并发症的管理:临床病例研究及文献综述

Yan, Huimin; Mo, Yunjun; Li, Yue; Li, Qian; Luo, Liping; Meng, Qing; Jia, Lei; Zhou, Lintao; Xiao, Lixia; Fu, Xiaoying

Seasonally and niche-differentiated diversity of active, dormant and dead microbes in coastal waters and surface sediments

沿海水域和表层沉积物中活性、休眠和死亡微生物的季节性和生态位分化多样性

Yu, Yunjun; Li, Guanzhe; Zhang, Haoyuan; Hu, Zeyu; Yu, Dirui; Gong, Jun

Integration of microbiome and transcriptome information in helping diagnosis of colorectal cancer

整合微生物组和转录组信息以辅助结直肠癌的诊断

He, Zhenyi; Zhu, Wenchuan; Zeng, Yunjun; Li, Sixian; Ma, Jun; Yang, Zhiyan; Wang, Haiyu; Zhang, Hongmei; Liu, Beixi; Wang, Tongmin

Self-Assembly of the Block Copolymer Containing Discotic Mesogens Driven by Liquid Crystalline Ordering Effect

液晶有序效应驱动的含盘状液晶基元嵌段共聚物的自组装

Hou, Xiaojian; Hu, Lingjuan; Yang, Huanzhi; Jin, Bixin; Luo, Yunjun; Li, Xiaoyu

Causal association between Parkinson's disease and cancer: a bidirectional Mendelian randomization study

帕金森病与癌症的因果关系:一项双向孟德尔随机化研究

Tang, Chunyan; Fu, Ping; Lin, Liangqing; Zhou, Hui; Huang, Yunjun; Li, Yang; Zhao, Sijun

Microbial characteristics of bile in gallstone patients: a comprehensive analysis of 9,939 cases

胆结石患者胆汁的微生物特征:一项对9939例病例的综合分析

Zheng, Xin; Yan, Yunjun; Li, Xin; Liu, Mimin; Zhao, Xiaoyue; He, Jing; Zhuang, Xuewei

Effects of microenvironment and biological behavior on the paracrine function of stem cells

微环境和生物学行为对干细胞旁分泌功能的影响

Xue, Zhixin; Liao, Yunjun; Li, Ye

A Bayesian network model for prediction of low or failed fertilization in assisted reproductive technology based on a large clinical real-world data

基于大型临床真实世界数据的贝叶斯网络模型用于预测辅助生殖技术中低受精率或受精失败率

Tian, Tian; Kong, Fei; Yang, Rui; Long, Xiaoyu; Chen, Lixue; Li, Ming; Li, Qin; Hao, Yongxiu; He, Yangbo; Zhang, Yunjun; Li, Rong; Wang, Yuanyuan; Qiao, Jie

Comparison of detection methods for carbonation depth of concrete

混凝土碳化深度检测方法的比较

Li, Bei; Tian, Ye; Zhang, Guoyi; Liu, Yu; Feng, Huiping; Jin, Nanguo; Jin, Xianyu; Wu, Hongxiao; Shao, Yinzhe; Yan, Dongming; Zhou, Zheng; Wang, Shenshan; Zhang, Zhiqiang; Chen, Jin; Chen, Xiaodong; Lu, Yunjun; Li, Xinyi; Wang, Jiaxi