Rheumatology

Multi-Omics Integration With Machine Learning Identified Early Diabetic Retinopathy, Diabetic Macula Edema and Anti-VEGF Treatment Response.

PURPOSE: Identify optimal metabolic features and pathways across diabetic retinopathy (DR) stages, develop risk models to differentiate diabetic macular edema (DME), and predict anti-vascular endothelial growth factor (anti-VEGF) therapy response.

MIMIC: Multimodal Islamophobic Meme Identification and Classification

Anti-Muslim hate speech has emerged within memes, characterized by context-dependent and rhetorical messages using text and images that seemingly mimic humor but convey Islamophobic sentiments. This work presents a novel dataset and proposes a classifier based on the Vision-and-Language Transformer (ViLT) specifically tailored to identify anti-Muslim hate within memes by integrating both visual ...

An evolving machine-learning-based algorithm to early predict response to anti-CGRP monoclonal antibodies in patients with migraine.

BACKGROUND: The present study aimed to determine whether machine-learning (ML)-based models can predict 3-, 6, and 12-month responses to the monoclona...

Deciphering the Role of SLFN12: A Novel Biomarker for Predicting Immunotherapy Outcomes in Glioma Patients Through Artificial Intelligence.

Gliomas are the most prevalent form of primary brain tumours. Recently, targeting the PD-1 pathway with immunotherapies has shown promise as a novel g...

Augmenting small biomedical datasets using generative AI methods based on self-organizing neural networks.

Small sample sizes in biomedical research often led to poor reproducibility and challenges in translating findings into clinical applications. This pr...

Machine learning-enabled virtual screening indicates the anti-tuberculosis activity of aldoxorubicin and quarfloxin with verification by molecular docking, molecular dynamics simulations, and biological evaluations.

Drug resistance in Mycobacterium tuberculosis (Mtb) is a significant challenge in the control and treatment of tuberculosis, making efforts to combat ...

A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma.

Recent studies suggest cGAS-STING pathway may play a crucial role in the genesis and development of hepatocellular carcinoma (HCC), closely associated...

Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics.

Recent advances in single-cell RNA-Sequencing (scRNA-Seq) technologies have revolutionized our ability to gather molecular insights into different phe...

Robust Steganography with Boundary-Preserving Overflow Alleviation and Adaptive Error Correction

With the rapid evolution of the Internet, the vast amount of data has created opportunities for fostering the development of steganographic techniqu...

Phenome-wide causal proteomics enhance systemic lupus erythematosus flare prediction: A study in Asian populations

Objective: Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by unpredictable flares. This study aimed to develop a n...

Hardness Results on Characteristics for Elastic-Degenerated Strings

Generalizations of plain strings have been proposed as a compact way to represent a collection of nearly identical sequences or to express uncertain...

Privacy-Preserving Graph-Based Machine Learning with Fully Homomorphic Encryption for Collaborative Anti-Money Laundering

Combating money laundering has become increasingly complex with the rise of cybercrime and digitalization of financial transactions. Graph-based mac...

Deep Learning to Discriminate Arteritic From Nonarteritic Ischemic Optic Neuropathy on Color Images.

IMPORTANCE: Prompt and accurate diagnosis of arteritic anterior ischemic optic neuropathy (AAION) from giant cell arteritis and other systemic vasculi...

On Novel Approach for Computing Distance based Indices of Anti-tuberculosis Drugs

This work aims to assess the molecular architectures of anti-tuberculosis drugs using both degree-based topological indices and novel distance based...

RS-MOCO: A deep learning-based topology-preserving image registration method for cardiac T1 mapping

Cardiac T1 mapping can evaluate various clinical symptoms of myocardial tissue. However, there is currently a lack of effective, robust, and efficie...

I Want to Break Free! Persuasion and Anti-Social Behavior of LLMs in Multi-Agent Settings with Social Hierarchy

As Large Language Model (LLM)-based agents become increasingly autonomous and will more freely interact with each other, studying interactions betwe...

Building Solidarity Amid Hostility: Experiences of Fat People in Online Communities

Online communities are important spaces for members of marginalized groups to organize and support one another. To better understand the experiences...

Identify As A Human Does: A Pathfinder of Next-Generation Anti-Cheat Framework for First-Person Shooter Games

The gaming industry has experienced substantial growth, but cheating in online games poses a significant threat to the integrity of the gaming exper...

Rise of the machines: how machine learning will shape the field of rheumatology.

A machine learning-based prediction model for gout in hyperuricemics: a nationwide cohort study.

OBJECTIVE: To develop a machine learning-based prediction model for identifying hyperuricemic participants at risk of developing gout.