FDA General

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis

The performance of visual anomaly inspection in industrial quality control is often constrained by the scarcity of real anomalous samples. Consequently, anomaly synthesis techniques have been developed to enlarge training sets and enhance downstream inspection. However, existing methods either suffer from poor integration caused by inpainting or fail to provide accurate masks. To address these lim...

The Mechanistic Invariance Test: Genomic Language Models Fail to Learn Positional Regulatory Logic

Genomic language models (gLMs) have transformed computational biology, achieving state-of-the-art performance across genomic tasks. Yet a fundamental question threatens the foundation of this success: do these models learn the mechanistic principles governing gene regulation, or do they merely exploit statistical shortcuts? We introduce the Mechanistic Invariance Test (MIT), a rigorous 650-sequenc...

PaveBench: A Versatile Benchmark for Pavement Distress Perception and Interactive Vision-Language Analysis

Pavement condition assessment is essential for road safety and maintenance. Existing research has made significant progress. However, most studies foc...

Measuring the Unmeasurable: A Diagnostic Sensor for AI Reasoning Pathology in Sequential Clinical Decision-Making

Large Language Models achieve impressive accuracy on medical benchmarks that present clinical information as complete vignettes, but their behavior un...

An Energy-Efficient Spiking Neural Network Architecture for Predictive Insulin Delivery

Diabetes mellitus affects over 537 million adults worldwide. Insulin-dependent patients require continuous glucose monitoring and precise dose calcula...

faers: A High-Fidelity Framework and R/Bioconductor Package for Precision Adverse Event Surveillance

Background: The FDA Adverse Event Reporting System (FAERS) is a critical pillar of post-marketing pharmacovigilance; however, its utility is constrain...

The false positive paradox: Examining real-world clinical predictive performance of FDA-authorized AI devices for radiology using clinical prevalence

The present study evaluates the real-world clinical predictive performance of FDA-authorized artificial intelligence (AI) devices used in radiology, f...

Deconvolution of omics data in Python with Deconomix -- cellular compositions, cell-type specific gene regulation, and background contributions

Background: Gene expression profiles derived from heterogeneous bulk samples contain signals from various cell populations. Cell-type deconvolution ap...

Novel 4D tensor decomposition-based approach integrating tri-omics profiling data can identify functionally relevant gene clusters

Integrating transcriptome, translatome, and proteome data remains challenging because changes in mRNA, ribosome occupancy, and protein abundance do no...

A 3D Reconstruction Benchmark for Asset Inspection

Asset management requires accurate 3D models to inform the maintenance, repair, and assessment of buildings, maritime vessels, and other key structure...

Using image classifiers to predict CMT2A disease-relevant mitochondrial motility phenotypes in iPSC motor neurons

Charcot-Marie-Tooth disease type 2A (CMT2A) is a genetic disease characterized by autosomal dominant MFN2 mutations and dysregulated mitochondrial tra...

A Self-Evolving Defect Detection Framework for Industrial Photovoltaic Systems

Reliable photovoltaic (PV) power generation requires timely detection of module defects that may reduce energy yield, accelerate degradation, and incr...

Automated Counting of Stacked Objects in Industrial Inspection

Visual object counting is a fundamental computer vision task in industrial inspection, where accurate, high-throughput inventory tracking and quality ...

Anterior's Approach to Fairness Evaluation of Automated Prior Authorization System

Increasing staffing constraints and turnaround-time pressures in Prior authorization (PA) have led to increasing automation of decision systems to sup...

Prompt-Driven Lightweight Foundation Model for Instance Segmentation-Based Fault Detection in Freight Trains

Accurate visual fault detection in freight trains remains a critical challenge for intelligent transportation system maintenance, due to complex opera...

A DNA foundation model predicts osteoporosis risk genes without proximity bias

Targets supported by human genetic associations are more than twice as likely to progress from clinical development to approval. Genome-wide associati...

Towards Cognitive Defect Analysis in Active Infrared Thermography with Vision-Text Cues

Active infrared thermography (AIRT) is currently witnessing a surge of artificial intelligence (AI) methodologies being deployed for automated subsurf...

From General-Purpose to Disease-Specific Features: Aligning LLM Embeddings on a Disease-Specific Biomedical Knowledge Graph for Drug Repurposing

Identifying new therapeutic uses for existing drugs is a major challenge in biomedicine, especially for complex neurodegenerative conditions such as A...

Artificial Intelligence Detects Cardiac Amyloidosis Before Clinical Diagnosis

The approval of novel disease-modifying treatments for cardiac amyloidosis (CA) offers an avenue to stabilize disease progression. Timely diagnosis of...

Gait-Related Digital Mobility Outcomes in Parkinson's Disease: New Insights into Convergent Validity?

Objective: In Parkinson's disease (PD), gait-related digital mobility outcomes (DMOs) show promise for monitoring mobility decline, but convergent val...