AIMC Topic: Lupus Erythematosus, Systemic
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Systemic lupus in the era of machine learning medicine.
Lupus science & medicine
Mar 4, 2024
Artificial intelligence and machine learning applications are emerging as transformative technologies in medicine. With greater access to a diverse range of big datasets, researchers are turning to these powerful techniques for data analysis. Machine...
Non-invasive prediction of the chronic degree of lupus nephropathy based on ultrasound radiomics.
Lupus
Dec 20, 2023
OBJECTIVE: Through machine learning (ML) analysis of the radiomics features of ultrasound extracted from patients with lupus nephritis (LN), this attempt was made to non-invasively predict the chronicity index (CI)of LN.
Profiling of kidney involvement in systemic lupus erythematosus by deep learning using the National Database of Designated Incurable Diseases of Japan.
Clinical and experimental nephrology
Mar 16, 2023
BACKGROUND: Kidney involvement frequently occurs in systemic lupus erythematosus (SLE), and its clinical manifestations are complicated. We profiled kidney involvement in SLE patients using deep learning based on data from the National Database of De...
Artificial intelligence and high-dimensional technologies in the theragnosis of systemic lupus erythematosus.
The Lancet. Rheumatology
Feb 20, 2023
Systemic lupus erythematosus is a complex, systemic autoimmune disease characterised by immune dysregulation. Pathogenesis is multifactorial, contributing to clinical heterogeneity and posing challenges for diagnosis and treatment. Although strides i...
Comparing two machine learning approaches in predicting lupus hospitalization using longitudinal data.
Scientific reports
Sep 30, 2022
Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease characterized by flares ranging from mild to life-threatening. Severe flares and complications can require hospitalizations, which account for most of the direct costs of SLE ca...
Exploration of machine learning methods to predict systemic lupus erythematosus hospitalizations.
Lupus
Jul 14, 2022
OBJECTIVES: Systemic lupus erythematosus (SLE) is a heterogeneous disease characterized by disease flares which can require hospitalization. Our objective was to apply machine learning methods to predict hospitalizations for SLE from electronic healt...
A deep learning-based smartphone platform for cutaneous lupus erythematosus classification assistance: Simplifying the diagnosis of complicated diseases.
Journal of the American Academy of Dermatology
Feb 19, 2021
Machine learning approaches to predict lupus disease activity from gene expression data.
Scientific reports
Jul 3, 2019
The integration of gene expression data to predict systemic lupus erythematosus (SLE) disease activity is a significant challenge because of the high degree of heterogeneity among patients and study cohorts, especially those collected on different mi...
Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB): characterizing clusters of differentiation within a compendium of systemic lupus erythematosus patients.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
Clusters of differentiation () are cell surface biomarkers that denote key biological differences between cell types and disease state. CD-targeting therapeutic monoclonal antibodies () afford rich trans-disease repositioning opportunities. Within a ...
Biomarkers of erosive arthritis in systemic lupus erythematosus: Application of machine learning models.
PloS one
Dec 4, 2018
OBJECTIVE: Limited evidences are available on biomarkers to recognize Systemic Lupus erythematosus (SLE) patients at risk to develop erosive arthritis. Anti-citrullinated peptide antibodies (ACPA) have been widely investigated and identified in up to...
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