Rheumatology

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 complication. This study aimed to compare logistic regression, random forest, and gradient boosting models to predict amyloidosis in FMF patients. METHODS: Patients with FMF diagnosed between 1990 and 2022 at Cerrahpaşa Faculty of Medicine were retros...

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, antithyroid drugs (ATDs), and surgery representing the mainstay of therapy, with variation in their use over time and geographic location. Hypothyroidism has been an accepted tradeoff in many cases, though recently there are increased concerns about altered qu...

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...

Artificial Intelligence in Systemic Sclerosis: Clinical applications, challenges, and future directions.

Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal...

Phenotypic response surface-guided pharmacotherapy for personalized combination treatment in complex diseases.

INTRODUCTION: Optimizing multidrug regimens for complex diseases remains a major challenge in precision medicine because responses are shaped by inter...

Digital experts for fibromyalgia: A comparative analysis of ChatGPT, Gemini, and DeepSeek in addressing patient questions with focus on readability and medical accuracy.

BackgroundPatients with fibromyalgia require clear and reliable medical information to manage a complex chronic condition. AI-based tools may offer va...

Explainable machine learning for predicting infections that require hospitalization in patients with systemic lupus erythematosus.

OBJECTIVES: To develop and validate an explainable artificial intelligence (XAI)-based machine learning (ML) model for predicting infections requiring...

Unraveling defect-mediated ion transport behavior in anti-perovskite solid-state electrolytes via machine learning molecular dynamics simulations.

Anti-perovskite (AP) solid-state electrolytes (SSEs) have emerged as promising candidates for high-safety solid-state batteries due to their wide elec...

Machine learning-based prediction of multi-level antimicrobial resistance in Klebsiella pneumoniae using whole-genome sequencing data.

OBJECTIVES: In this study, we developed an integrated approach for accurate and comprehensive prediction of anti-microbial resistance (AMR) using whol...

Fluid Volumes Longitudinal Modeling to Predict Atrophy and Fibrosis in Neovascular Age-Related Macular Degeneration.

PURPOSE: To evaluate the impact of retinal fluid volumes on the development of atrophy and fibrosis in neovascular age-related macular degeneration (n...

Dataset of manually curated peptides against arthropod-borne viruses.

Anti-arboviral peptides are biomolecules capable of interfering with key stages of the arboviral lifecycle. We present a dataset compiling 270 peptide...

From pathogenesis to precision medicine in systemic lupus erythematosus: Emerging biomarkers and targeted interventions.

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease characterized by immune dysregulation, autoantibody production, and chron...

Predicting Molecular Laser Properties from First-Principles Using Machine Learning-Based Nuclear Ensemble Approach Spectra.

The accurate prediction of absorption and emission spectra of molecular compounds using quantum mechanical (QM) methods is essential for understanding...

A global perspective on autoimmunity and immunodeficiency: exploring geoepidemiology trends.

Autoimmune and primary immunodeficiency disorders represent a growing global health burden influenced by a complex interplay of genetic, environmental...

Automated Molecular Design in BRADSHAW, Applied to the Optimization of ERAP1 Inhibitors.

Generative design and machine learning are increasingly prevalent in medicinal chemistry. To pilot the comprehensive use of automated molecular design...

Using causal machine learning and real world data to improve dose response decision making for secukinumab in psoriatic arthritis.

Personalized treatment in psoriatic arthritis (PsA) remains challenging, particularly in guiding dose escalation decisions. We applied a causal machin...

Surgically Relevant Knee Phenotypes: The Modified Coronal Plane Alignment of the Knee (mCPAK) System - A Deep Learning-based Classification.

BACKGROUND: The coronal plane alignment of the knee (CPAK) classification proposes nine knee phenotypes based on constitutional limb alignment and joi...

Challenges and Controversies in the Diagnosis and Management of Thymic Epithelial Tumors from the Thymic Tumor Subcommittee of the International Association for the Study of Lung Cancer Rare Tumors Committee.

Thymic epithelial tumors (TETs), comprising thymomas, thymic carcinomas, and thymic neuroendocrine neoplasms, are rare prevascular (anterior) mediasti...

A machine-learning-based tool for stroke risk prediction in blunt cerebrovascular injury: development and preliminary evaluation.

PURPOSE: Stroke risk correlates with the Biffl grading system in blunt cerebrovascular injury (BCVI). Although anti-thrombotic therapy is the mainstay...