FDA General

Drug-Target Interaction/Affinity Prediction: Deep Learning Models and Advances Review

Drug discovery remains a slow and expensive process that involves many steps, from detecting the target structure to obtaining approval from the Food and Drug Administration (FDA), and is often riddled with safety concerns. Accurate prediction of how drugs interact with their targets and the development of new drugs by using better methods and technologies have immense potential to speed up this...

Bridge the Gaps between Machine Unlearning and AI Regulation

The "right to be forgotten" and the data privacy laws that encode it have motivated machine unlearning since its earliest days. Now, an inbound wave of artificial intelligence regulations - like the European Union's Artificial Intelligence Act (AIA) - potentially offer important new use cases for machine unlearning. However, this position paper argues, this opportunity will only be realized if r...

Vision-Language In-Context Learning Driven Few-Shot Visual Inspection Model

We propose general visual inspection model using Vision-Language Model~(VLM) with few-shot images of non-defective or defective products, along with...

Deep Learning in Automated Power Line Inspection: A Review

In recent years, power line maintenance has seen a paradigm shift by moving towards computer vision-powered automated inspection. The utilization of...

HODDI: A Dataset of High-Order Drug-Drug Interactions for Computational Pharmacovigilance

Drug-side effect research is vital for understanding adverse reactions arising in complex multi-drug therapies. However, the scarcity of higher-orde...

Improved YOLOv5s model for key components detection of power transmission lines

High-voltage transmission lines are located far from the road, resulting in inconvenient inspection work and rising maintenance costs. Intelligent i...

DeepFRC: An End-to-End Deep Learning Model for Functional Registration and Classification

Functional data - observations in the form of curves or trajectories - arise in diverse domains such as biomedical sensing, motion capture, and hand...

EdgeMLOps: Operationalizing ML models with Cumulocity IoT and thin-edge.io for Visual quality Inspection

This paper introduces EdgeMLOps, a framework leveraging Cumulocity IoT and thin-edge.io for deploying and managing machine learning models on resour...

Bridging spatial and temporal scales of developmental gene regulation

The development of multicellular organisms relies on the precise coordination of molecular events across multiple spatial and temporal scales. Under...

Regulatory Science Innovation for Generative AI and Large Language Models in Health and Medicine: A Global Call for Action

The integration of generative AI (GenAI) and large language models (LLMs) in healthcare presents both unprecedented opportunities and challenges, ne...

Enhancing Visual Inspection Capability of Multi-Modal Large Language Models on Medical Time Series with Supportive Conformalized and Interpretable Small Specialized Models

Large language models (LLMs) exhibit remarkable capabilities in visual inspection of medical time-series data, achieving proficiency comparable to h...

Beyond Benchmarks: On The False Promise of AI Regulation

The rapid advancement of artificial intelligence (AI) systems in critical domains like healthcare, justice, and social services has sparked numerous...

Visual Localization via Semantic Structures in Autonomous Photovoltaic Power Plant Inspection

Inspection systems utilizing unmanned aerial vehicles (UAVs) equipped with thermal cameras are increasingly popular for the maintenance of photovolt...

Effective Defect Detection Using Instance Segmentation for NDI

Ultrasonic testing is a common Non-Destructive Inspection (NDI) method used in aerospace manufacturing. However, the complexity and size of the ultr...

Machine Learning-Driven Convergence Analysis in Multijurisdictional Compliance Using BERT and K-Means Clustering

Digital data continues to grow, there has been a shift towards using effective regulatory mechanisms to safeguard personal information. The CCPA of ...

Adapting OpenAI's CLIP Model for Few-Shot Image Inspection in Manufacturing Quality Control: An Expository Case Study with Multiple Application Examples

This expository paper introduces a simplified approach to image-based quality inspection in manufacturing using OpenAI's CLIP (Contrastive Language-...

FDA Perspective on the Regulation of Artificial Intelligence in Health Care and Biomedicine.

IMPORTANCE: Advances in artificial intelligence (AI) must be matched by efforts to better understand and evaluate how AI performs across health care a...

Anomaly Detection for Industrial Applications, Its Challenges, Solutions, and Future Directions: A Review

Anomaly detection from images captured using camera sensors is one of the mainstream applications at the industrial level. Particularly, it maintain...

Multi-Modal Attention Networks for Enhanced Segmentation and Depth Estimation of Subsurface Defects in Pulse Thermography

AI-driven pulse thermography (PT) has become a crucial tool in non-destructive testing (NDT), enabling automatic detection of hidden anomalies in va...

Sequential PatchCore: Anomaly Detection for Surface Inspection using Synthetic Impurities

The appearance of surface impurities (e.g., water stains, fingerprints, stickers) is an often-mentioned issue that causes degradation of automated v...