AIMC Topic: Neural Networks, Computer

Clear Filters Showing 29481 to 29490 of 31376 articles

Artificial Intelligence-based Analytics for Diagnosis of Small Bowel Enteropathies and Black Box Feature Detection.

Journal of pediatric gastroenterology and nutrition
OBJECTIVES: Striking histopathological overlap between distinct but related conditions poses a disease diagnostic challenge. There is a major clinical need to develop computational methods enabling clinicians to translate heterogeneous biomedical ima...

Probabilistic Contextual and Structural Dependencies Learning in Grammar-Based Genetic Programming.

Evolutionary computation
Genetic Programming is a method to automatically create computer programs based on the principles of evolution. The problem of deceptiveness caused by complex dependencies among components of programs is challenging. It is important because it can mi...

An improved Faster R-CNN for defect recognition of key components of transmission line.

Mathematical biosciences and engineering : MBE
In a national power grid system, it is necessary to keep transmission lines secure. Detection and identification must be regularly performed for transmission tower components. In this paper, we propose a defect recognition method for key components o...

Federated Deep Learning Architecture for Personalized Healthcare.

Studies in health technology and informatics
Using deep learning to advance personalized healthcare requires data about patients to be collected and aggregated from disparate sources that often span institutions and geographies. Researchers regularly come face-to-face with legitimate security a...

Using Deep Learning for Individual-Level Predictions of Adherence with Growth Hormone Therapy.

Studies in health technology and informatics
The problem of consistent therapy adherence is a current challenge for health informatics, and its solution can increase the success rate of treatments. Here we show a methodology to predict, at individual-level, future therapy adherence for patients...

Deep Neural Network Driven Speech Classification for Relevance Detection in Automatic Medical Documentation.

Studies in health technology and informatics
The automation of medical documentation is a highly desirable process, especially as it could avert significant temporal and monetary expenses in healthcare. With the help of complex modelling and high computational capability, Automatic Speech Recog...

COVID-19 Image Segmentation Based on Deep Learning and Ensemble Learning.

Studies in health technology and informatics
Medical imaging offers great potential for COVID-19 diagnosis and monitoring. Our work introduces an automated pipeline to segment areas of COVID-19 infection in CT scans using deep convolutional neural networks. Furthermore, we evaluate the performa...

GAN-Based Prediction of Time Series.

Studies in health technology and informatics
The study aims at generating initial and directional insights in the applicability of conditional recurrent generative adversarial nets for the imputation and forecasting of medical time series data. Our experiment with blood pressure series showed t...

Semantic Anomaly Detection in Medical Time Series.

Studies in health technology and informatics
The main goal of this project was to define and evaluate a new unsupervised deep learning approach that can differentiate between normal and anomalous intervals of signals like the electrical activity of the heart (ECG). Denoising autoencoders based ...

GraphDTA: predicting drug-target binding affinity with graph neural networks.

Bioinformatics (Oxford, England)
SUMMARY: The development of new drugs is costly, time consuming and often accompanied with safety issues. Drug repurposing can avoid the expensive and lengthy process of drug development by finding new uses for already approved drugs. In order to rep...