Rheumatology

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 problem stems from limited study resources, rare diseases, ethical considerations in animal studies, costly expert diagnosis, and others. As a contribution to the problem, we propose a novel generative algorithm based on self-organizing maps (SOMs) to ...

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 the spread of this global health burden more difficult. To accelerate anti-tuberculosis drug discovery, repurposing clinically approved or investigational drugs for the treatment of tuberculosis by computational methods has become an attractive strat...

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.

Applying Machine Learning for Prescriptive Support: A Use Case with Unfractionated Heparin in Intensive Care Units.

Continuous unfractionated heparin is widely used in intensive care, yet its complex pharmacokinetic properties complicate the determination of appropr...

Exploring Offline Large Language Models for Clinical Information Extraction: A Study of Renal Histopathological Reports of Lupus Nephritis Patients.

Open source, lightweight and offline generative large language models (LLMs) hold promise for clinical information extraction due to their suitability...

A Comprehensive Natural Language Processing Pipeline for the Chronic Lupus Disease.

Electronic Health Records (EHRs) contain a wealth of unstructured patient data, making it challenging for physicians to do informed decisions. In this...

[Soil Cadmium Prediction and Health Risk Assessment of an Oasis on the Eastern Edge of the Tarim Basin Based on Feature Optimization and Machine Learning].

Soil heavy metal pollution poses a serious threat to food security, human health, and soil ecosystems. Based on 644 soil samples collected from a typi...