Lupus Erythematosus, Systemic

Evaluating large language models as a supplementary patient information resource on antimalarial use in systemic lupus erythematosus.

Lupus 40013495

ObjectiveTo assess the accuracy, completeness, and reproducibility of Large Language Models (LLMs) (Copilot, GPT-3.5, and GPT-4) on antimalarial use in systemic lupus erythematosus (SLE).Materials and MethodsWe utilized 13 questions derived from pati...

Antimalarials Female Humans Language Large Language Models Lupus Erythematosus, Systemic Male Patient Education as Topic Reproducibility of Results Surveys and Questionnaires

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Fatigue Detection with Machine Learning Approaches using Data from Wearable Devices.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 40031477

Severe and chronic fatigue is one of the top symptoms in patients with non-communicable chronic immune-mediated inflammatory diseases like Systemic Lupus Erythematosus (SLE) and Sjögren's disease (SjD). The majority of fatigue assessment approaches r...

Accelerometry Adult Fatigue Female Humans Lupus Erythematosus, Systemic Machine Learning Male Middle Aged Wearable Electronic Devices

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Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics.

Briefings in bioinformatics 39814561

Recent advances in single-cell RNA-Sequencing (scRNA-Seq) technologies have revolutionized our ability to gather molecular insights into different phenotypes at the level of individual cells. The analysis of the resulting data poses significant chall...

Algorithms Alzheimer Disease COVID-19 Deep Learning Gene Expression Profiling Humans Lupus Erythematosus, Systemic Neural Networks, Computer Phenotype SARS-CoV-2 Sequence Analysis, RNA Single-Cell Analysis Transcriptome

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Identification of glucocorticoid-related genes in systemic lupus erythematosus using bioinformatics analysis and machine learning.

PloS one 40131879

BACKGROUND: Systemic lupus erythematosus (SLE) is a complex autoimmune disease that has significant impacts on patients' quality of life and poses a substantial economic burden on society.

Case-Control Studies Cluster Analysis Computational Biology Gene Expression Profiling Gene Regulatory Networks Glucocorticoids Humans Lupus Erythematosus, Systemic Machine Learning Molecular Docking Simulation Transcriptome

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Identification of common diagnostic genes and molecular pathways in endometriosis and systemic lupus erythematosus by machine learning approach and in vitro experiment.

International journal of medical sciences 39744159

Growing research suggests that endometriosis and systemic lupus erythematosus (SLE) are both chronic inflammatory diseases and closely related, but no studies have explored their common molecular characteristics and underlying mechanisms. Based on GE...

Endometriosis Female Gene Expression Profiling Gene Regulatory Networks Humans Lupus Erythematosus, Systemic Machine Learning MicroRNAs Nomograms ROC Curve

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Machine Learning-Based Identification of Novel Exosome-Derived Metabolic Biomarkers for the Diagnosis of Systemic Lupus Erythematosus and Differentiation of Renal Involvement.

Current medical science 40019633

OBJECTIVE: This study aims to investigate the exosome-derived metabolomics profiles in systemic lupus erythematosus (SLE), identify differential metabolites, and analyze their potential as diagnostic markers for SLE and lupus nephritis (LN).

Adult Biomarkers Case-Control Studies Diagnosis, Differential Exosomes Female Humans Lupus Erythematosus, Systemic Lupus Nephritis Machine Learning Male Metabolomics Middle Aged ROC Curve Support Vector Machine Tandem Mass Spectrometry

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Disease diagnostics using machine learning of B cell and T cell receptor sequences.

Science (New York, N.Y.) 39977494

Clinical diagnosis typically incorporates physical examination, patient history, various laboratory tests, and imaging studies but makes limited use of the human immune system's own record of antigen exposures encoded by receptors on B cells and T ce...

Autoimmune Diseases B-Lymphocytes COVID-19 Diabetes Mellitus, Type 1 HIV Infections Humans Infections Influenza, Human Lupus Erythematosus, Systemic Machine Learning Receptors, Antigen, B-Cell Receptors, Antigen, T-Cell SARS-CoV-2

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Prediction of mortality risk in critically ill patients with systemic lupus erythematosus: a machine learning approach using the MIMIC-IV database.

Lupus science & medicine 39947742

OBJECTIVE: Early prediction of long-term outcomes in patients with systemic lupus erythematosus (SLE) remains a great challenge in clinical practice. Our study aims to develop and validate predictive models for the mortality risk.

Adult Area Under Curve Critical Illness Databases, Factual Female Humans Logistic Models Lupus Erythematosus, Systemic Machine Learning Male Middle Aged Nomograms Risk Assessment Risk Factors ROC Curve

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Application of machine learning in assessing disease activity in SLE.

Lupus science & medicine 40204296

OBJECTIVE: SLE is a chronic autoimmune disease with immune complex deposition in various organs, causing inflammation. The Systemic Lupus Erythematosus Disease Activity Index 2000 assesses disease severity but is subjective. This study aimed to const...

Adult Algorithms Antibodies, Antinuclear Female Humans Lupus Erythematosus, Systemic Machine Learning Male Middle Aged Neutrophils Retrospective Studies ROC Curve Severity of Illness Index Young Adult

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Integrated bioinformatics, machine learning, and molecular docking reveal crosstalk genes and potential drugs between periodontitis and systemic lupus erythematosus.

Scientific reports 40328806

Evidence indicates a connection between periodontitis (PD) and systemic lupus erythematosus (SLE), though the underlying co-morbid mechanisms remain unclear. This study sought to identify the genetic factors and potential therapeutic agents involved ...

Computational Biology Databases, Genetic Gene Expression Profiling Gene Regulatory Networks Humans Lupus Erythematosus, Systemic Machine Learning Molecular Docking Simulation Periodontitis Protein Interaction Maps

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Evaluating large language models as a supplementary patient information resource on antimalarial use in systemic lupus erythematosus.

Fatigue Detection with Machine Learning Approaches using Data from Wearable Devices.

Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics.

Identification of glucocorticoid-related genes in systemic lupus erythematosus using bioinformatics analysis and machine learning.

Identification of common diagnostic genes and molecular pathways in endometriosis and systemic lupus erythematosus by machine learning approach and in vitro experiment.

Machine Learning-Based Identification of Novel Exosome-Derived Metabolic Biomarkers for the Diagnosis of Systemic Lupus Erythematosus and Differentiation of Renal Involvement.

Disease diagnostics using machine learning of B cell and T cell receptor sequences.

Prediction of mortality risk in critically ill patients with systemic lupus erythematosus: a machine learning approach using the MIMIC-IV database.

Application of machine learning in assessing disease activity in SLE.

Integrated bioinformatics, machine learning, and molecular docking reveal crosstalk genes and potential drugs between periodontitis and systemic lupus erythematosus.

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