FDA General

Patient Reactions to Artificial Intelligence-Clinician Discrepancies: Web-Based Randomized Experiment.

BACKGROUND: As the US Food and Drug Administration (FDA)-approved use of artificial intelligence (AI) for medical imaging rises, radiologists are increasingly integrating AI into their clinical practices. In lung cancer screening, diagnostic AI offers a second set of eyes with the potential to detect cancer earlier than human radiologists. Despite AI's promise, a potential problem with its integra...

Transparency in Healthcare AI: Testing European Regulatory Provisions against Users' Transparency Needs

Artificial Intelligence (AI) plays an essential role in healthcare and is pervasively incorporated into medical software and equipment. In the European Union, healthcare is a high-risk application domain for AI, and providers must prepare Instructions for Use (IFU) according to the European regulation 2024/1689 (AI Act). To this regulation, the principle of transparency is cardinal and requires ...

GNNs and ensemble models enhance the prediction of new sRNA-mRNA interactions in unseen conditions.

Bacterial small RNAs (sRNAs) are pivotal in post-transcriptional regulation, affecting functions like virulence, metabolism, and gene expression by bi...

Semantically-driven Deep Reinforcement Learning for Inspection Path Planning

This paper introduces a novel semantics-aware inspection planning policy derived through deep reinforcement learning. Reflecting the fact that withi...

Paradigm Shift in Infrastructure Inspection Technology: Leveraging High-performance Imaging and Advanced AI Analytics to Inspect Road Infrastructure

Effective road infrastructure management is crucial for modern society. Traditional manual inspection techniques remain constrained by cost, efficie...

Enhancing Shape Perception and Segmentation Consistency for Industrial Image Inspection

Semantic segmentation stands as a pivotal research focus in computer vision. In the context of industrial image inspection, conventional semantic se...

Dumpling GNN: Hybrid GNN Enables Better ADC Payload Activity Prediction Based on the Chemical Structure.

Antibody-drug conjugates (ADCs) are promising cancer therapeutics, but optimizing their cytotoxic payloads remains challenging. We present DumplingGNN...

BoostDILI: Extreme Gradient Boost-Powered Drug-Induced Liver Injury Prediction and Structural Alerts Generation.

Over the past 60 years, drug-induced liver injury (DILI) has played a key role in the withdrawal of marketed drugs due to safety concerns. Early predi...

Framework of Voting Prediction of Parliament Members

Keeping track of how lawmakers vote is essential for government transparency. While many parliamentary voting records are available online, they are...

A High-Performance Thermal Infrared Object Detection Framework with Centralized Regulation

Thermal Infrared (TIR) technology involves the use of sensors to detect and measure infrared radiation emitted by objects, and it is widely utilized...

A roadmap for safe, regulation-compliant Living Labs for AI and digital health development.

Safe and agile experimentation spaces are essential for developing AI-enabled medical devices and digital health innovations. "Living Labs" offer a co...

Automated Caries Detection Under Dental Restorations and Braces Using Deep Learning.

In the dentistry field, dental caries is a common issue affecting all age groups. The presence of dental braces and dental restoration makes the detec...

Integrating bioinformatics and machine learning to identify glomerular injury genes and predict drug targets in diabetic nephropathy.

Diabetes mellitus (DM) is a chronic metabolic disorder that poses significant challenges to public health. Among its various complications, diabetic n...

Shining a Light on the Future of Biophotonics.

Biophotonics-the interdisciplinary fusion of light-based technologies with biology and medicine-is rapidly transforming research, diagnostics, and the...

Generative Deep Learning Design of Single-Domain Antibodies Against Venezuelan Equine Encephalitis Virus.

BACKGROUND/OBJECTIVES: Venezuelan equine encephalitis virus (VEEV) represents a significant biothreat with no FDA-approved vaccine currently available...

The Environment-Dependent Regulatory Landscape of the E. coli Genome

All cells respond to changes in both their internal milieu and the environment around them through the regulation of their genes. Despite decades of...

Interpreting Deep Learning Studies in Glaucoma: Unresolved Challenges.

Deep learning algorithms as tools for automated image classification have recently experienced rapid growth in imaging-dependent medical specialties, ...

Synthetic Similarity Search in Automotive Production

Visual quality inspection in automotive production is essential for ensuring the safety and reliability of vehicles. Computer vision (CV) has become...

Comparison of Deep Transfer Learning Against Contrastive Learning in Industrial Quality Applications for Heavily Unbalanced Data Scenarios When Data Augmentation Is Limited.

AI-oriented quality inspection in manufacturing often faces highly imbalanced data, as defective products are rare, and there are limited possibilitie...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae famil...