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

Multi-Omics Analysis of the Immune Effect of the Engineered Exosome Drug Delivery System in Inducing Macrophage Apoptosis.

多组学分析工程化外泌体药物递送系统诱导巨噬细胞凋亡的免疫效应

Xiang Wei, Zhu Zhoujun, Shang Qisong, Yasin Parhat, Wu Yuanyuan, Song Xinghua

Mannosamine-Engineered Nanoparticles for Precision Rifapentine Delivery to Macrophages: Advancing Targeted Therapy Against Mycobacterium Tuberculosis

甘露糖胺工程纳米颗粒用于将利福喷汀精准递送至巨噬细胞:推进针对结核分枝杆菌的靶向治疗

Luan, Haopeng; Peng, Cong; Yasin, Parhat; Shang, Qisong; Xiang, Wei; Song, Xinghua

MRI-based deep learning with clinical and imaging features to differentiate medulloblastoma and ependymoma in children

结合临床和影像特征的基于磁共振成像的深度学习方法用于区分儿童髓母细胞瘤和室管膜瘤

Yimit, Yasen; Yasin, Parhat; Hao, Yue; Tuersun, Abudouresuli; Huang, Chencui; Zou, Xiaoguang; Qiu, Ya; Wang, Yunling; Nijiati, Mayidili

Decoding the exosomal nucleic acid delivery system axis of macrophage autophagy and immune reprogramming via multi-omics analysis.

通过多组学分析解码巨噬细胞自噬和免疫重编程的外泌体核酸递送系统轴。

Zhu Zhoujun, Xiang Wei, Zhang Pengchao, Yasin Parhat, Song Xinghua

Mannosamine-Modified Poly(lactic-co-glycolic acid)-Polyethylene Glycol Nanoparticles for the Targeted Delivery of Rifapentine and Isoniazid in Tuberculosis Therapy

甘露糖胺修饰的聚乳酸-羟基乙酸共聚物-聚乙二醇纳米颗粒用于结核病治疗中利福喷丁和异烟肼的靶向递送

Peng, Cong; Luan, Haopeng; Shang, Qisong; Xiang, Wei; Yasin, Parhat; Song, Xinghua

Dual-center study on AI-driven multi-label deep learning for X-ray screening of knee abnormalities

一项关于人工智能驱动的多标签深度学习在膝关节异常X射线筛查中的双中心研究

Yasin, Parhat; Yimit, Yasen; Abulimiti, Abuduainijiang; Luan, Haopeng; Peng, Cong; Yakufu, Maihemuti; Song, Xinghua

Explainable machine learning for differential diagnosis of diabetic foot infection and osteomyelitis: a two-center study and clinically applicable web calculator using routine blood biomarkers

利用可解释机器学习方法鉴别诊断糖尿病足感染和骨髓炎:一项基于常规血液生物标志物的双中心研究及临床适用型网络计算器

Yasin, Parhat; Dong, Shiming; Aizezi, Zubaidanmu; Yimit, Yasen; Yusufu, Alimujiang; Yakufu, Maihemuti; Song, Xinghua

Comprehensive comparative analysis of explainable deep learning model for differentiation of brucellar spondylitis and tuberculous spondylitis through MRI sequences

基于MRI序列的布鲁氏菌性脊柱炎和结核性脊柱炎鉴别诊断中可解释深度学习模型的综合比较分析

Yasin, Parhat; Tuersun, Abudouresuli; Ashir, Anuar; Makhambetov, Yerlan; Sheng, Jie; Song, Xinghua

Machine Learning-Based Interpretable Screening for Osteoporosis in Tuberculosis Spondylitis Patients Using Blood Test Data: Development and External Validation of a Novel Web-Based Risk Calculator with Explainable Artificial Intelligence (XAI)

基于机器学习的结核性脊柱炎患者骨质疏松症可解释筛查:利用血液检测数据开发和外部验证一种新型的基于网络的、具有可解释人工智能(XAI)的风险计算器

Yasin, Parhat; Ding, Liwen; Mamat, Mardan; Guo, Wei; Song, Xinghua

Development and validation of an interpretable nomogram for predicting the risk of the prolonged postoperative length of stay for tuberculous spondylitis: a novel approach for risk stratification

开发和验证可解释的列线图,用于预测结核性脊柱炎术后住院时间延长的风险:一种新的风险分层方法

Yasin, Parhat; Luan, Haopeng; Peng, Cong; Song, Xinghua