Jichong Zhu

发表

Machine learning-based clustering in cervical spondylotic myelopathy patients to identify heterogeneous clinical characteristics

Xinli Zhan, Wenkang Chen, Jiarui Chen, 2022, Frontiers in Surgery.

Immune cell infiltration-related clinical diagnostic model for Ankylosing Spondylitis

Xinli Zhan, Jiarui Chen, Chenxing Zhou, 2022, Frontiers in Genetics.

Upregulated of ANXA3, SORL1, and Neutrophils May Be Key Factors in the Progressionof Ankylosing Spondylitis

Xinli Zhan, Hao Li, Jiarui Chen, 2022, Frontiers in Immunology.

A Predictive Clinical-Radiomics Nomogram for Differentiating Tuberculous Spondylitis from Pyogenic Spondylitis Using CT and Clinical Risk Factors

Xinli Zhan, Hao Li, Chenxing Zhou, 2022, Infection and drug resistance.

Identification of clinical heterogeneity and construction of a novel subtype predictive model in patients with ankylosing spondylitis: An unsupervised machine learning study.

Xinli Zhan, Jiarui Chen, Chenxing Zhou, 2023, International immunopharmacology.

Development and Validation of a Machine Learning-Based Nomogram for Prediction of Ankylosing Spondylitis

Xinli Zhan, Hao Li, Wenkang Chen, 2022, Rheumatology and Therapy.

Dysregulation of SAA1, TUBA8 and Monocytes Are Key Factors in Ankylosing Spondylitis With Femoral Head Necrosis

Xinli Zhan, Jiarui Chen, Jie Jiang, 2022, Frontiers in Immunology.

Comprehensive AI-assisted tool for ankylosing spondylitis based on multicenter research outperforms human experts

Xinli Zhan, Hao Li, Jiarui Chen, 2023, Frontiers in Public Health.

Difference between the blood samples of patients with bone and joint tuberculosis and patients with tuberculosis studied using machine learning

Xinli Zhan, Hao Li, Jiarui Chen, 2023, Frontiers in Surgery.

Application of machine learning in prediction of bone cement leakage during single-level thoracolumbar percutaneous vertebroplasty

Xinli Zhan, Zhenwei Yang, Hao Li, 2023, BMC Surgery.

Proteomic analysis to identification of hypoxia related markers in spinal tuberculosis: a study based on weighted gene co-expression network analysis and machine learning

Xinli Zhan, Chenxing Zhou, Jie Jiang, 2023, BMC Medical Genomics.

Predictive Value of Machine Learning Models in Postoperative Mortality of Older Adults Patients with Hip Fracture: A Systematic Review and Meta-analysis.

F. Liu, Jichong Zhu, Xiaoju Tang, 2023, Archives of gerontology and geriatrics (Print).

MMP9 and STAT1 are biomarkers of the change in immune infiltration after anti-tuberculosis therapy, and the immune status can identify patients with spinal tuberculosis.

Xinli Zhan, Wenkang Chen, Jiarui Chen, 2023, International immunopharmacology.

Identification of spinal tuberculosis subphenotypes using routine clinical data: a study based on unsupervised machine learning

Lu Liu, Xinli Zhan, Chenxing Zhou, 2023, Annals of medicine.

Using Machine Learning to Predict Surgical Site Infection After Lumbar Spine Surgery

Xinli Zhan, Chenxing Zhou, Chong Liu, 2023, Infection and drug resistance.

Network pharmacology combined with molecular docking and experimental validation to explore the potential mechanism of Cinnamomi ramulus against ankylosing spondylitis.

Xinli Zhan, Chenxing Zhou, Chong Liu, 2023, Annals of medicine.

Development and validation of a machine learning-based nomogram for predicting HLA-B27 expression

Xinli Zhan, Chenxing Zhou, Chong Liu, 2023, BMC Immunology.

Elucidating the causal nexus between antibody-mediated immunity and autoimmune diseases: Insights from bidirectional mendelian randomization, gene expression profiling, and drug sensitivity analysis.

Xinli Zhan, Jiarui Chen, Chenxing Zhou, 2024, International immunopharmacology.

Development and validation of a risk nomogram to estimate risk of hyponatremia after spinal cord injury: A retrospective single-center study.

Yiji Su, Jichong Zhu, Jiling Wang, 2024, The journal of spinal cord medicine.

Epidemiological characteristics of ankylosing spondylitis in Guangxi Province of China from 2014 to 2021

Shenmin Zhang, Xinli Zhan, Jiarui Chen, 2023, Archives of medical science : AMS.