Machine learning techniques for personalised medicine approaches in immune-mediated chronic inflammatory diseases: applications and challenges
In the past decade, the emergence of machine learning (ML) applications has led to
significant advances towards implementation of personalised medicine approaches for …
significant advances towards implementation of personalised medicine approaches for …
An update on the management of childhood-onset systemic lupus erythematosus
Childhood-onset systemic lupus erythematosus (cSLE) is a prototype of a multisystemic,
inflammatory, heterogeneous autoimmune condition. This disease is characterized by …
inflammatory, heterogeneous autoimmune condition. This disease is characterized by …
Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients
Abstract Background The SARS-CoV-2 pandemic is currently leading to increasing numbers
of COVID-19 patients all over the world. Clinical presentations range from asymptomatic …
of COVID-19 patients all over the world. Clinical presentations range from asymptomatic …
Dimensionality reduction by UMAP reinforces sample heterogeneity analysis in bulk transcriptomic data
Transcriptomic analysis plays a key role in biomedical research. Linear dimensionality
reduction methods, especially principal-component analysis (PCA), are widely used in …
reduction methods, especially principal-component analysis (PCA), are widely used in …
The pathogenesis of systemic lupus erythematosus: harnessing big data to understand the molecular basis of lupus
Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease that causes
damage to multiple organ systems. Despite decades of research and available murine …
damage to multiple organ systems. Despite decades of research and available murine …
The promise of precision medicine in rheumatology
Systemic autoimmune rheumatic diseases (SARDs) exhibit extensive heterogeneity in
clinical presentation, disease course, and treatment response. Therefore, precision …
clinical presentation, disease course, and treatment response. Therefore, precision …
An introduction to machine learning and analysis of its use in rheumatic diseases
Abstract Machine learning (ML) is a computerized analytical technique that is being
increasingly employed in biomedicine. ML often provides an advantage over explicitly …
increasingly employed in biomedicine. ML often provides an advantage over explicitly …
Multiclass wound image classification using an ensemble deep CNN-based classifier
Acute and chronic wounds are a challenge to healthcare systems around the world and
affect many people's lives annually. Wound classification is a key step in wound diagnosis …
affect many people's lives annually. Wound classification is a key step in wound diagnosis …
Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes
Objectives A novel longitudinal clustering technique was applied to comprehensive
autoantibody data from a large, well-characterised, multinational inception systemic lupus …
autoantibody data from a large, well-characterised, multinational inception systemic lupus …
Disease-associated and patient-specific immune cell signatures in juvenile-onset systemic lupus erythematosus: patient stratification using a machine-learning …
Background Juvenile-onset systemic lupus erythematosus (SLE) is a rare autoimmune
rheumatic disease characterised by more severe disease manifestations, earlier damage …
rheumatic disease characterised by more severe disease manifestations, earlier damage …