Infectious Disease

COVID-19

Latest AI and machine learning research in covid-19 for healthcare professionals.

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Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features.

BACKGROUND AND OBJECTIVE: Radiomics and deep learning have emerged as two distinct approaches to med...

Artificial Intelligence Technologies for COVID-19 De Novo Drug Design.

The recent covid crisis has provided important lessons for academia and industry regarding digital r...

A radiomics-boosted deep-learning model for COVID-19 and non-COVID-19 pneumonia classification using chest x-ray images.

PURPOSE: To develop a deep learning model design that integrates radiomics analysis for enhanced per...

Transferable Neural Network Potential Energy Surfaces for Closed-Shell Organic Molecules: Extension to Ions.

Transferable high dimensional neural network potentials (HDNNPs) have shown great promise as an aven...

Deep Learning-Based Computer-Aided Pneumothorax Detection Using Chest X-ray Images.

Pneumothorax is a thoracic disease leading to failure of the respiratory system, cardiac arrest, or ...

A hybrid machine learning/deep learning COVID-19 severity predictive model from CT images and clinical data.

COVID-19 clinical presentation and prognosis are highly variable, ranging from asymptomatic and pauc...

PhosVarDeep: deep-learning based prediction of phospho-variants using sequence information.

Human DNA sequencing has revealed numerous single nucleotide variants associated with complex diseas...

Gauging the Impact of Artificial Intelligence and Mathematical Modeling in Response to the COVID-19 Pandemic: A Systematic Review.

While the world continues to grapple with the devastating effects of the SARS-nCoV-2 virus, differen...

An Ensemble Learning Model for COVID-19 Detection from Blood Test Samples.

Current research endeavors in the application of artificial intelligence (AI) methods in the diagnos...

DeepCAGE: Incorporating Transcription Factors in Genome-wide Prediction of Chromatin Accessibility.

Although computational approaches have been complementing high-throughput biological experiments for...

Augmented Graph Neural Network with hierarchical global-based residual connections.

Graph Neural Networks (GNNs) are powerful architectures for learning on graphs. They are efficient f...

Metaheuristics based COVID-19 detection using medical images: A review.

Many countries in the world have been facing the rapid spread of COVID-19 since February 2020. There...

An automated diagnosis and classification of COVID-19 from chest CT images using a transfer learning-based convolutional neural network.

Researchers have developed more intelligent, highly responsive, and efficient detection methods owin...

CPG-based generation strategy of variable rhythmic chewing movements for a dental testing chewing robot.

The rhythmic chewing movement pattern is dynamically reshaped to adapt to a variable chewing environ...

Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany.

During 2020, the infection rate of COVID-19 has been investigated by many scholars from different re...

TSFD-Net: Tissue specific feature distillation network for nuclei segmentation and classification.

Nuclei segmentation and classification of hematoxylin and eosin-stained histology images is a challe...

Long short-term memory model - A deep learning approach for medical data with irregularity in cancer predication with tumor markers.

BACKGROUND: Machine learning (ML) has emerged as a superior method for the analysis of large dataset...

Testing a global null hypothesis using ensemble machine learning methods.

Testing a global null hypothesis that there are no significant predictors for a binary outcome of in...

Supervised and weakly supervised deep learning models for COVID-19 CT diagnosis: A systematic review.

Artificial intelligence (AI) and computer vision (CV) methods become reliable to extract features fr...

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