Rheumatology

CARS-AMP: A Simple and Efficient Deep Learning Model for Antimicrobial Peptide Prediction.

With the increase in global antibiotic resistance, there is an urgent demand for antibiotic substitutes, for which antimicrobial peptides (AMPs) have attracted a lot of attention due to their unique mechanism of action that makes it difficult for bacteria to develop drug resistance. Beyond the natural discovery of AMPs, artificial intelligence techniques have become powerful tools to explore large...

Balancing Speed and Sensitivity: Echo-Planar Accelerated MRI for ARIA-H Screening in Anti-Aβ Therapeutics.

The recent advent of anti-amyloid-β monoclonal antibodies has introduced new demands for MRI-based screening of amyloid-related imaging abnormalities, particularly the hemorrhage subtype (ARIA-H). In this editorial, we discuss the study by Loftus and colleagues, which evaluates the diagnostic performance of echo-planar accelerated gradient-recalled echo (GRE) and susceptibility-weighted imaging (S...

Multivariate Pattern Analysis Identifies Potential Intertrial Resting-State EEG Biomarkers in Fibromyalgia.

Fibromyalgia involves widespread musculoskeletal pain and hypersensitivity, often accompanied by neurological, cognitive, and affective disturbances. ...

The Role of Artificial Intelligence Algorithms in Challenging Diagnostic Cases - Between Potential and Real Clinical Support.

INTRODUCTION: Extranodal natural killer/T-cell lymphoma, nasal type (ENKTL), is a rare EBV-associated malignancy characterized by destructive tumors i...

The evolving role of artificial intelligence in optimizing treatment and patient selection in diabetic macular edema.

Anti-vascular endothelial growth factor (anti-VEGF) therapy is the mainstay of management for diabetic macular edema (DME), but marked variability in ...

Anti-vascular endothelial growth factor therapy for posterior segment diseases: Progress, challenges, and the road ahead.

The emergence of anti-vascular endothelial growth factor (anti-VEGF) therapy has marked a paradigm shift in the treatment of retinal and choroidal vas...

Markerless gait analysis for children and adolescents with juvenile idiopathic arthritis using a machine learning pipeline.

BACKGROUND: Musculoskeletal diseases, such as Juvenile Idiopathic Arthritis (JIA), can lead to altered joint mobility and changes in gait pattern. Whi...

Precision Medicine in Autoimmune Thyroid Diseases: Decoding Biomarkers, Targeted Therapies and Digital Innovation.

INTRODUCTION: Autoimmune thyroid diseases (AITDs), including Graves' disease and Hashimoto's thyroiditis, arise from genetic, epigenetic, and environm...

Elucidating the anti-colorectal cancer mechanism of Physalis Calyx seu Fructus extract via mass spectrometry-molecular networking and bioinformatics.

Chemical profiling combined with computational analysis highlighted luteolin and chrysoeriol as candidate anti-colorectal cancer (CRC) compounds in Ph...

The needle study: Machine learning as a new method for case-finding in celiac disease.

OBJECTIVES: Despite a well-defined diagnostic work-up, uncertainties persist regarding celiac disease (CeD) detection strategies in the general popula...

Automated Eosinophil Quantification Using Deep Learning to Predict Therapy Escalation in Pediatric Ulcerative Colitis.

BACKGROUND: Emerging evidence implicates eosinophils as important modulators of disease activity and therapeutic response in ulcerative colitis. Autom...

Validity and applicability of machine learning models for systemic lupus erythematosus diagnosis.

BACKGROUND: The diagnosis of systemic lupus erythematosus (SLE) is clinically complex, and early identification is essential for timely intervention a...

Deep learning discriminates seizures from normal brain oscillations in the electroencephalogram of a rat model of post-traumatic epilepsy.

This study used machine learning to objectively identify seizures in the electroencephalogram of a model of post-traumatic epilepsy based on fluid per...

Brain PET in the era of anti-amyloid-β antibody therapy for Alzheimer disease.

Here the current and emerging roles of brain positron emission tomography (PET) in Alzheimer's disease (AD) in the era of anti-amyloid-β antibody ther...

Adaptive neighborhood aggregation graph neural network for early diagnosis of Alzheimer's disease.

Early diagnosis of Alzheimer's disease (AD) is crucial for timely intervention but remains challenging due to subtle and heterogeneous brain alteratio...

Comprehensive analysis of predictive models for disease manifestations and case fatality in systemic lupus erythematosus.

This systematic review evaluated the performance and risk of bias in Systemic Lupus Erythematosus (SLE) disease manifestations and case fatality predi...

Amyloidosis secondary to familial Mediterranean fever: machine learning-based prediction models.

OBJECTIVES: Familial Mediterranean Fever (FMF) is a monogenic autoinflammatory disease caused by MEFV mutations, with amyloidosis as its most severe c...

Graves' disease: a new era of pathophysiology-guided therapeutics.

Graves' disease (GD) is an autoimmune entity that had an unchanged treatment paradigm for more than half a century with radioactive iodine, antithyroi...

autoscoRA: Deep Learning to Automate Sharp/van der Heijde Scoring of Radiographic Damage in Rheumatoid Arthritis.

OBJECTIVE: Regular imaging by conventional radiography to assess for joint damage is a cornerstone in the management of rheumatoid arthritis (RA). Sco...

Multi-class classification of autoimmune skin disease by efficient localization of overlapped lesion boundaries using SAM.

BACKGROUND: Detection of Autoimmune skin disease is found challenging due to overlapping features and irregular skin lesion boundaries. Although numer...