Lupus

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 with classical pathways and tumor immunity. We aimed to develop models predicting survival and anti-PD-1/PD-L1 outcomes centered on the cGAS-STING pathway in HCC. We identified classical pathways highly correlated with cGAS-STING pathway and constru...

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 phenotypes at the level of individual cells. The analysis of the resulting data poses significant challenges, and proper statistical methods are required to analyze and extract information from scRNA-Seq datasets. Sample classification based on gene exp...

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...

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...

ZIF-90 treats fungal keratitis by promoting macrophage apoptosis and inhibiting inflammatory response

Fungal keratitis is a severe vision-threatening corneal infection with a prognosis influenced by fungal virulence and the host's immune defense mech...

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...

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...

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 ...

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 ...

Fatigue Detection with Machine Learning Approaches using Data from Wearable Devices.

Severe and chronic fatigue is one of the top symptoms in patients with non-communicable chronic immune-mediated inflammatory diseases like Systemic Lu...

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...

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...