Rheumatology

Artificial intelligence and machine learning in rheumatology.

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

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.

Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancer.

With the ever-increasing number of artificial intelligence (AI) systems, mitigating risks associated with their use has become one of the most urgent ...

A deep learning approach to direct immunofluorescence pattern recognition in autoimmune bullous diseases.

BACKGROUND: Artificial intelligence (AI) is reshaping healthcare, using machine and deep learning (DL) to enhance disease management. Dermatology has ...

Bursting the bubble on diagnostics: artificial intelligence in autoimmune bullous disease.

An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis.

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease during childhood and adolescence. The temporomandibular joints (TMJ) are amon...

Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests.

Deep learning models are being adopted and applied across various critical medical tasks, yet they are primarily trained to provide point predictions ...

Freq-Mip-AA : Frequency Mip Representation for Anti-Aliasing Neural Radiance Fields

Neural Radiance Fields (NeRF) have shown remarkable success in representing 3D scenes and generating novel views. However, they often struggle with ...

Histopathology Based AI Model Predicts Anti-Angiogenic Therapy Response in Renal Cancer Clinical Trial

Predictive biomarkers of treatment response are lacking for metastatic clear cell renal cell carcinoma (ccRCC), a tumor type that is treated with an...

[An artificial neural network diagnostic model for scleroderma and immune cell infiltration analysis based on mitochondria-associated genes].

OBJECTIVE: To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related g...

Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer.

Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demons...

The Florida Scoring System for stratifying children with suspected Sjögren's disease: a cross-sectional machine learning study.

BACKGROUND: Childhood Sjögren's disease is a rare, underdiagnosed, and poorly-understood condition. By integrating machine learning models on a paedia...

Analysis of Emerging Variants of Turkey Reovirus using Machine Learning.

Avian reoviruses continue to cause disease in turkeys with varied pathogenicity and tissue tropism. Turkey enteric reovirus has been identified as a c...

Characterizing Anti-Vaping Posts for Effective Communication on Instagram Using Multimodal Deep Learning.

INTRODUCTION: Instagram is a popular social networking platform for sharing photos with a large proportion of youth and young adult users. We aim to i...

AgeAnnoMO: a knowledgebase of multi-omics annotation for animal aging.

Aging entails gradual functional decline influenced by interconnected factors. Multiple hallmarks proposed as common and conserved underlying denomina...

MACC: a visual interactive knowledgebase of metabolite-associated cell communications.

Metabolite-associated cell communications play critical roles in maintaining the normal biological function of human through coordinating cells, organ...

ChatGPT's accuracy and patient-oriented answers about fibromyalgia.

PD-1 Targeted Antibody Discovery Using AI Protein Diffusion.

The programmed cell death protein 1 (PD-1, CD279) is an important therapeutic target in many oncological diseases. This checkpoint protein inhibits T ...

Artificial Intelligence Application for Anti-tumor Drug Synergy Prediction.

Currently, the main therapeutic methods for cancer include surgery, radiation therapy, and chemotherapy. However, chemotherapy still plays an importan...

USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING APPROACHES TO ENHANCE CANCER THERAPY AND DRUG DISCOVERY: A NARRATIVE REVIEW.

BACKGROUND: This paper looks at how AI and machine learning have been applied over the last ten years to the development of anti-cancer drugs. By spee...