ArticleFrontiers in psychiatry2021
Relevant Characteristics Analysis Using Natural Language Processing and Machine Learning Based on Phenotypes and T-Cell Subsets in Systemic Lupus Erythematosus Patients With Anxiety.
Article in Frontiers in psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.
- The application of artificial intelligence in systemic lupus erythematosus: a bibliometric analysis of current trends and future directions.Frontiers in medicine · 2026Pooled it
- Organ-based characterization of B cells in patients with systemic lupus erythematosus.Frontiers in immunology · 2025Pooled it
- Genetically determined causality between immune cells and anxiety disorders: A Mendelian randomization study.Medicine · 2026Article
- Artificial intelligence in immunotherapy: revolutionizing diagnostic and therapeutic applications in cancer and autoimmune diseases.Clinical and experimental medicine · 2026Review
- CD4Neurobiology of stress · 2024Article
- Systemic lupus in the era of machine learning medicine.Lupus science & medicine · 2024Review
- SVM-Based Model Combining Patients' Reported Outcomes and Lymphocyte Phenotypes of Depression in Systemic Lupus Erythematosus.Biomolecules · 2023Article
- Application of Machine Learning Models in Systemic Lupus Erythematosus.International journal of molecular sciences · 2023Review
- Identification of key genes in late-onset major depressive disorder through a co-expression network module.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Anxiety is frequently observed in patients with systemic lupus erythematosus (SLE) and the immune system could act as a trigger for anxiety. To recognize abnormal T-cell and B-cell subsets for SLE patients with anxiety, in this study, patient disease phenotypes data from electronic lupus symptom records were extracted by using natural language processing. The Hospital Anxiety and Depression Scale (HADS) was used to distinguish patients, and 107 patients were selected to meet research requirements. Then, peripheral blood was collected from two patient groups for multicolor flow cytometry experiments. The characteristics of 75 T-cell and 15 B-cell subsets were investigated between SLE patients with- (
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Registered trials
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