FDA General

Demographics, Overlap, and Latency of Severe Cutaneous Adverse Reactions in an FDA Database

Severe cutaneous adverse reactions (SCARs), including Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS-TEN), drug reaction with eosinophilia and systemic symptoms (DRESS), acute generalized exanthematous pustulosis (AGEP), and generalized bullous fixed drug eruption (GBFDE), are rare but life-threatening drug hypersensitivity syndromes. Due to their low incidence and diagnostic complexity,...

Machine Learning-Based Prediction of Cell-type Resolved Brain eQTLs Enhances Discovery of Variants Explaining Alzheimer’s Disease Heritability

The majority of causal genome-wide association studies (GWAS) variants for Alzheimer’s disease (AD) are believed to reside in noncoding regions of the genome, where they likely affect gene regulation, particularly in microglia. Although expression Quantitative Trait Loci (eQTL) studies offer valuable insights into gene regulation, they tend to identify variants in the promoter regions of genes und...

Quantifying the severity of patient safety events via statistical natural language processing

Medical errors are one of the leading causes of death in the United States. Several public databases have been built to record patient safety events a...

Broad-spectrum coronavirus inhibitors discovered by modeling viral fusion dynamics.

Development of oral, broad-spectrum therapeutics targeting SARS-CoV-2, its variants, and related coronaviruses could curb the spread of COVID-19 and a...

m5CStack: An integrated framework for m5C site prediction using multi-feature stacking.

RNA 5-methylcytosine (m5C) modification sites are essential for understanding the regulation of RNA functions in various biological processes. However...

Integrated irrigation of water and fertilizer with superior self-correcting fuzzy PID control system.

To address the fixed-parameter limitations of traditional PID control (e.g., excessive overshoot, prolonged settling time, poor adaptability to nonlin...

Developing a machine learning algorithm to predict psychotropic drugs-induced weight gain and the effectiveness of anti-obesity drugs in patients with severe mental illness: Protocol for a prospective cohort study.

Obesity is a global public health concern, often co-occurring in patients with severe mental illnesses. The impact of psychotropic drugs-induced weigh...

Implications of An Evolving Regulatory Landscape on the Development of AI and ML in Medicine.

The rapid advancement of artificial intelligence and machine learning (AI/ML) technologies in healthcare presents significant opportunities for enhanc...

Artificial intelligence and food flavor: How AI models are shaping the future and revolutionary technologies for flavor food development.

The food flavor science, traditionally reliant on experimental methods, is now entering a promising era with the help of artificial intelligence (AI)....

A Machine Learning Algorithm to Predict Medical Device Recall by the Food and Drug Administration.

INTRODUCTION: Medical device recalls are important to the practice of emergency medicine, as unsafe devices include many ubiquitous items in emergency...

Regulating radiology AI medical devices that evolve in their lifecycle

Over time, the distribution of medical image data drifts due to factors such as shifts in patient demographics, acquisition devices, and disease man...

TPepPro: a deep learning model for predicting peptide-protein interactions.

MOTIVATION: Peptides and their derivatives hold potential as therapeutic agents. The rising interest in developing peptide drugs is evidenced by incre...

Detecting and Classifying Defective Products in Images Using YOLO

With the continuous advancement of industrial automation, product quality inspection has become increasingly important in the manufacturing process....

Adapting Segment Anything Model (SAM) to Experimental Datasets via Fine-Tuning on GAN-based Simulation: A Case Study in Additive Manufacturing

Industrial X-ray computed tomography (XCT) is a powerful tool for non-destructive characterization of materials and manufactured components. XCT com...

Generative AI regulation can learn from social media regulation

There is strong agreement that generative AI should be regulated, but strong disagreement on how to approach regulation. While some argue that AI re...

Bayesian inference of mean velocity fields and turbulence models from flow MRI

We solve a Bayesian inverse Reynolds-averaged Navier-Stokes (RANS) problem that assimilates mean flow data by jointly reconstructing the mean flow f...

How Learner Control and Explainable Learning Analytics on Skill Mastery Shape Student Desires to Finish and Avoid Loss in Tutored Practice

Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that suppo...

Accelerating Manufacturing Scale-Up from Material Discovery Using Agentic Web Navigation and Retrieval-Augmented AI for Process Engineering Schematics Design

Process Flow Diagrams (PFDs) and Process and Instrumentation Diagrams (PIDs) are critical tools for industrial process design, control, and safety. ...

Reinforcement Learning for Freeway Lane-Change Regulation via Connected Vehicles

Lane change decision-making is a complex task due to intricate vehicle-vehicle and vehicle-infrastructure interactions. Existing algorithms for lane...

Thermal and RGB Images Work Better Together in Wind Turbine Damage Detection

The inspection of wind turbine blades (WTBs) is crucial for ensuring their structural integrity and operational efficiency. Traditional inspection m...