Lupus

Development and Validation of Machine Learning Models for Predicting Mortality in Hospitalised Systemic Lupus Erythematosus Patients in Dr. Sardjito Hospital, Indonesia Machine Learning Prediction of In-Hospital Mortality in SLE

Objectives This study aimed to develop and validate machine learning models to predict in-hospital mortality among systemic lupus erythematosus (SLE) patients using administrative claims data in a tertiary referral center in Indonesia. Methods We conducted a retrospective cohort study of 327 SLE hospital admissions between January 2019 and June 2025. Predictor variables included demographics, hosp...

Do Larger Models Really Win in Drug Discovery?A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction

The rapid growth of molecular foundation models and general-purpose large language models has encouraged a scale-centric view of artificial intelligence in drug discovery, in which larger pretrained models are expected to supersede compact cheminformatics models and task-specific graph neural networks (GNNs). We test this assumption on 22 molecular property and activity endpoints, including public...

Multi-Modal Deep Learning Integrates Spatial Topologies and Sequential Motifs to Identify Class I HDAC Inhibitors as Pan-Cancer Therapeutics

The molecular characterization of human solid growths has introduced immense genomic complexity and intra-tumoral diversification. Converting these de...

Semaglutide is associated with improved breast cancer survival, lower metastatic burden, and a dose-survival relationship uncoupled from weight-loss magnitude

Metabolic dysfunction is increasingly recognized as a risk factor for poor outcomes in breast cancer, but whether incretin-based therapies confer surv...

Performance Anomaly Detection in Athletics: A Benchmarking System with Visual Analytics

Anti-doping programs rely on biological testing to detect performance-enhancing drugs, but such testing costs over $800 per sample and is limited by s...

Robust by Design: A Continuous Monitoring and Data Integration Framework for Medical AI

Adaptive medical AI models often face performance drops in dynamic clinical environments due to data drift. We propose an autonomous continuous monito...

Domain-generalizable Face Anti-Spoofing with Patch-based Multi-tasking and Artifact Pattern Conversion

Face Anti-Spoofing (FAS) algorithms, designed to secure face recognition systems against spoofing, struggle with limited dataset diversity, impairing ...

Shortcut Learning in Glomerular AI: Adversarial Penalties Hurt, Entropy Helps

Stain variability is a pervasive source of distribution shift and potential shortcut learning in renal pathology AI. We ask whether lupus nephritis gl...

Universal computational thermal imaging overcoming the ghosting effect

Thermal imaging is crucial for night vision but fundamentally hampered by the ghosting effect, a loss of detailed texture in cluttered photon streams....

DPD-Cancer: Explainable Graph-based Deep Learning for Small Molecule Anti-Cancer Activity Prediction

Accurate drug response prediction is a critical bottleneck in computational biochemistry, limited by the challenge of modelling the interplay between ...

SDD-YOLO: A Small-Target Detection Framework for Ground-to-Air Anti-UAV Surveillance with Edge-Efficient Deployment

Detecting small unmanned aerial vehicles (UAVs) from a ground-to-air (G2A) perspective presents significant challenges, including extremely low pixel ...

Fully Automated Abstraction of Longitudinal Breast Oncology Records with Off-The-Shelf Large Language Models

Background: Manual chart abstraction is a major bottleneck in clinical research. In oncology, important outcomes such as disease recurrence and the tr...

Anti-I2V: Safeguarding your photos from malicious image-to-video generation

Advances in diffusion-based video generation models, while significantly improving human animation, poses threats of misuse through the creation of fa...

Vision-Language Attribute Disentanglement and Reinforcement for Lifelong Person Re-Identification

Lifelong person re-identification (LReID) aims to learn from varying domains to obtain a unified person retrieval model. Existing LReID approaches typ...

From Metabolomics to Function: Ranking Plant Stem Cell Metabolomes for Use in Health and Cosmetics

Background: Plants produce diverse metabolites with potential benefits for human health. However, the metabolomes of plant callus cultures-cell cultur...

Deep Learning-Based Airway Segmentation in Systemic Lupus Erythematosus Patients with Interstitial Lung Disease (SLE-ILD): A Comparative High-Resolution CT Analysis

To characterize lobar and segmental airway volume differences between systemic lupus erythematosus (SLE) patients with interstitial lung disease (ILD)...

Rational Design of Selective IL-2-based Activators for CAR T Cells Using AlphaFold3 and Physics-Informed Machine Learning

Recombinant human Interleukin-2 (rhIL-2, Aldesleukin) is used in immunotherapy for metastatic melanoma and renal cell carcinoma. Low-dose IL-2 has bee...

Experimental multi-center validation of a radiomics-based photonic quantum precision medicine architecture for lesion-level prediction of anti-PD-1 response in non-small cell lung cancer

Background: Previous research has shown that radiomics-based machine learning models are promising precision medicine tools for lesion-level predictio...

A fast and accurate calculation method for light induced isomerization of retinal proteins in real time

Retinal is a chromophore covalently bound to various photoreceptors. Its photo-induced isomerization triggers a series of structural changes named pho...

AI-Guided CRISPR Screen Accelerates Discovery of New Drug Targets

Psoriasis affects over 125 million people worldwide, yet the mechanistic understanding of keratinocyte-driven inflammation remains incomplete, limitin...