FDA General

Explainability and causability for artificial intelligence-supported medical image analysis in the context of the European In Vitro Diagnostic Regulation.

Artificial Intelligence (AI) for the biomedical domain is gaining significant interest and holds considerable potential for the future of healthcare, particularly also in the context of in vitro diagnostics. The European In Vitro Diagnostic Medical Device Regulation (IVDR) explicitly includes software in its requirements. This poses major challenges for In Vitro Diagnostic devices (IVDs) that invo...

iProm-Zea: A two-layer model to identify plant promoters and their types using convolutional neural network.

A promoter is a short DNA sequence near the start codon, responsible for initiating the transcription of a specific gene in the genome. The accurate recognition of promoters is important for achieving a better understanding of transcriptional regulation. Because of their importance in the process of biological transcriptional regulation, there is an urgent need to develop in silico tools to identi...

Multilevel Structural Components Detection and Segmentation toward Computer Vision-Based Bridge Inspection.

Bridge inspection plays a critical role in mitigating the safety risks associated with bridge deterioration and decay. CV (computer vision) technology...

Pressure vessel-oriented visual inspection method based on deep learning.

The detection of surface parameters of pressure vessel welds guarantees safe operation. To address the problems of low efficiency and poor accuracy of...

An Optimized BP Neural Network Model and Its Application in the Credit Evaluation of Venture Loans.

With the rapid development of entrepreneurship loans in China, the construction of a credit evaluation system of risk loans has become an important fi...

Robotised Geometric Inspection of Thin-Walled Aerospace Casings.

This paper deals with the development of dimensional control technology for the production of ADT (accessory drive train) gearbox housing. The project...

In silico prediction of potential drug-induced nephrotoxicity with machine learning methods.

In recent years, drug-induced nephrotoxicity has been one of the main reasons for the failure of drug development. Early prediction of the nephrotoxic...

UV/VIS imaging-based PAT tool for drug particle size inspection in intact tablets supported by pattern recognition neural networks.

The potential of machine vision systems has not currently been exploited for pharmaceutical applications, although expected to provide revolutionary s...

The Need for Medical Artificial Intelligence That Incorporates Prior Images.

The use of artificial intelligence (AI) has grown dramatically in the past few years in the United States and worldwide, with more than 300 AI-enabled...

Discovery of moiety preference by Shapley value in protein kinase family using random forest models.

BACKGROUND: Human protein kinases play important roles in cancers, are highly co-regulated by kinase families rather than a single kinase, and complem...

FCNGRU: Locating Transcription Factor Binding Sites by Combing Fully Convolutional Neural Network With Gated Recurrent Unit.

Deciphering the relationship between transcription factors (TFs) and DNA sequences is very helpful for computational inference of gene regulation and ...

Real-Time Artificial Intelligence-Based Optical Diagnosis of Neoplastic Polyps during Colonoscopy.

BACKGROUND: Artificial intelligence using computer-aided diagnosis (CADx) in real time with images acquired during colonoscopy may help colonoscopists...

Deep learning-based anomaly detection from ultrasonic images.

Non-destructive testing is a group of methods for evaluating the integrity of components. Among them, ultrasonic inspection stands out due to its abil...

Photo-induced non-volatile VO phase transition for neuromorphic ultraviolet sensors.

In the quest for emerging in-sensor computing, materials that respond to optical stimuli in conjunction with non-volatile phase transition are highly ...

Domain Adapted Deep-Learning for Improved Ultrasonic Crack Characterization Using Limited Experimental Data.

Deep learning is an effective method for ultrasonic crack characterization due to its high level of automation and accuracy. Simulating the training s...

Robot-assisted, real-time, MRI-guided laser interstitial thermal therapy for pediatric patients with hypothalamic hamartoma: surgical technique, pitfalls, and initial results.

OBJECTIVE: Real-time, MRI-guided laser interstitial thermal therapy (MRgLITT) has been reported as a safe and effective technique for the treatment of...

The current status of breakthrough devices designation in the United States and innovative medical devices designation in Korea for digital health software.

INTRODUCTION: Artificial Intelligence (AI) is becoming increasingly utilized in the medical device industry as it can address unmet demands in clinica...

[Artificial Intelligence: Infrastructures and Prerequisites at European Level].

The application of artificial intelligence (AI) is often associated with the use of large amounts of data for the construction of AI models and algori...

A clinical evaluation study of cardiothoracic ratio measurement using artificial intelligence.

BACKGROUND: Artificial intelligence, particularly the deep learning (DL) model, can provide reliable results for automated cardiothoracic ratio (CTR) ...

Attention Module Magnetic Flux Leakage Linked Deep Residual Network for Pipeline In-Line Inspection.

Pipeline operational safety is the foundation of the pipeline industry. Inspection and evaluation of defects is an important means of ensuring the saf...