AIMC Topic: Lupus Erythematosus, Systemic

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A Comprehensive Natural Language Processing Pipeline for the Chronic Lupus Disease.

Studies in health technology and informatics
Electronic Health Records (EHRs) contain a wealth of unstructured patient data, making it challenging for physicians to do informed decisions. In this paper, we introduce a Natural Language Processing (NLP) approach for the extraction of therapies, d...

Identification of novel biomarkers for childhood-onset systemic lupus erythematosus using machine learning algorithms and immune infiltration analysis.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Childhood-onset systemic lupus erythematosus (cSLE) is a chronic autoimmune disease that is often more severe than adult-onset SLE and is challenging to diagnose due to its variable presentation and lack of specific diagnostic tests.

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
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...

Automated and flexible identification of complex disease: building a model for systemic lupus erythematosus using noisy labeling.

Journal of the American Medical Informatics Association : JAMIA
UNLABELLED: Accurate and efficient identification of complex chronic conditions in the electronic health record (EHR) is an important but challenging task that has historically relied on tedious clinician review and oversimplification of the disease....