AIMC Topic: Lupus Erythematosus, Systemic

Clear Filters Showing 31 to 40 of 54 articles

Comparing two machine learning approaches in predicting lupus hospitalization using longitudinal data.

Scientific reports
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
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...

Machine learning approaches to predict lupus disease activity from gene expression data.

Scientific reports
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
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
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...

Predicting hospital readmission for lupus patients: An RNN-LSTM-based deep-learning methodology.

Computers in biology and medicine
Hospital readmission is one of the critical metrics used for measuring the performance of hospitals. The HITECH Act imposes penalties when patients are readmitted to hospitals if they are diagnosed with one of the six conditions mentioned in the Act....

Diagnostic utility of serum melatonin levels in systemic lupus erythematosus: a case-control study.

Reumatismo
Systemic lupus erythematosus (SLE) is a chronic systemic autoimmune inflammatory disease and early diagnosis is of clinical and therapeutic importance. Melatonin is an endogenous endolamine hormone that plays an important role in the immune system du...

Characterizing Autoimmune Disease-associated Diffuse Large B-cell Lymphoma in a SEER-Medicare Cohort.

Clinical lymphoma, myeloma & leukemia
BACKGROUND: Severe immune dysregulation such as seen in autoimmune (AI) disease is known to act as a significant risk factor for diffuse large B-cell lymphoma (DLBCL). However, little is known about the demographics or clinical outcomes of DLBCL that...

Word2Vec inversion and traditional text classifiers for phenotyping lupus.

BMC medical informatics and decision making
BACKGROUND: Identifying patients with certain clinical criteria based on manual chart review of doctors' notes is a daunting task given the massive amounts of text notes in the electronic health records (EHR). This task can be automated using text cl...