COVID-19

Technological Innovation in Outpatient Assistance for Chronic Liver Disease and Liver Transplant Patients During the Coronavirus Disease Outbreak: A Method to Minimize Transmission.

Modeling the Spread of COVID-19 Infection Using a Multilayer Perceptron.

Coronavirus (COVID-19) is a highly infectious disease that has captured the attention of the worldwide public. Modeling of such diseases can be extremely important in the prediction of their impact. While classic, statistical, modeling can provide satisfactory models, it can also fail to comprehend the intricacies contained within the data. In this paper, authors use a publicly available dataset, ...

A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy.

BACKGROUND: For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complete response (pCR; no invasive or in situ) cannot be...

Robotics Utilization for Healthcare Digitization in Global COVID-19 Management.

This paper describes the evolving role of robotics in healthcare and allied areas with special concerns relating to the management and control of the ...

Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications.

Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new...

Using X-ray images and deep learning for automated detection of coronavirus disease.

Coronavirus is still the leading cause of death worldwide. There are a set number of COVID-19 test units accessible in emergency clinics because of th...

Combining gene expression profiling and machine learning to diagnose B-cell non-Hodgkin lymphoma.

Non-Hodgkin B-cell lymphomas (B-NHLs) are a highly heterogeneous group of mature B-cell malignancies. Their classification thus requires skillful eval...

Detection of Depression and Scaling of Severity Using Six Channel EEG Data.

Depression is a psychiatric problem which affects the growth of a person, like how a person thinks, feels and behaves. The major reason behind wrong d...

Artificial intelligence may offer insight into factors determining individual TSH level.

The factors that determine Serum Thyrotropin (TSH) levels have been examined through different methods, using different covariates. However, the use o...

T-Net: Nested encoder-decoder architecture for the main vessel segmentation in coronary angiography.

In this paper, we proposed nested encoder-decoder architecture named T-Net. T-Net consists of several small encoder-decoders for each block constituti...

Strategies to modulate zebrafish collective dynamics with a closed-loop biomimetic robotic system.

The objective of this study is to integrate biomimetic robots into small groups of zebrafish and to modulate their collective behaviours. A possible a...

Similarity-Based Methods and Machine Learning Approaches for Target Prediction in Early Drug Discovery: Performance and Scope.

Computational methods for predicting the macromolecular targets of drugs and drug-like compounds have evolved as a key technology in drug discovery. H...

Stochastic quasi-gradient methods: variance reduction via Jacobian sketching.

We develop a new family of variance reduced stochastic gradient descent methods for minimizing the average of a very large number of smooth functions....

The usefulness of the Deep Learning method of variational autoencoder to reduce measurement noise in glaucomatous visual fields.

The aim of the study was to investigate the usefulness of processing visual field (VF) using a variational autoencoder (VAE). The training data consis...

COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System.

Background Chest radiography may play an important role in triage for coronavirus disease 2019 (COVID-19), particularly in low-resource settings. Purp...

Predicting COVID-19 in China Using Hybrid AI Model.

The coronavirus disease 2019 (COVID-19) breaking out in late December 2019 is gradually being controlled in China, but it is still spreading rapidly i...

COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches.

Coronavirus causes a wide variety of respiratory infections and it is an RNA-type virus that can infect both humans and animal species. It often cause...

Modeling the trend of coronavirus disease 2019 and restoration of operational capability of metropolitan medical service in China: a machine learning and mathematical model-based analysis.

BACKGROUND: To contain the outbreak of coronavirus disease 2019 (COVID-19) in China, many unprecedented intervention measures are adopted by the gover...

Diagnosis of Coronavirus Disease 2019 (COVID-19) With Structured Latent Multi-View Representation Learning.

Recently, the outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly across the world. Due to the large number of infected patients and he...

Deep learning-based multi-view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study.

PURPOSE: To develop a deep learning-based method to assist radiologists to fast and accurately identify patients with COVID-19 by CT images.