COVID-19

A Novel Framework Based on Deep Learning and ANOVA Feature Selection Method for Diagnosis of COVID-19 Cases from Chest X-Ray Images.

. The new coronavirus disease (known as COVID-19) was first identified in Wuhan and quickly spread worldwide, wreaking havoc on the economy and people's everyday lives. As the number of COVID-19 cases is rapidly increasing, a reliable detection technique is needed to identify affected individuals and care for them in the early stages of COVID-19 and reduce the virus's transmission. The most access...

Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features.

This paper puts forward a new method of landscape recognition and evaluation by using aerial video and EEG technology. In this study, seven typical landscape types (forest, wetland, grassland, desert, water, farmland, and city) were selected. Different electroencephalogram (EEG) signals were generated through different inner experiences and feelings felt by people watching video stimuli of the dif...

Bayesian-based optimized deep learning model to detect COVID-19 patients using chest X-ray image data.

Coronavirus Disease 2019 (COVID-19) is extremely infectious and rapidly spreading around the globe. As a result, rapid and precise identification of C...

ECG-BiCoNet: An ECG-based pipeline for COVID-19 diagnosis using Bi-Layers of deep features integration.

The accurate and speedy detection of COVID-19 is essential to avert the fast propagation of the virus, alleviate lockdown constraints and diminish the...

A 12-hospital prospective evaluation of a clinical decision support prognostic algorithm based on logistic regression as a form of machine learning to facilitate decision making for patients with suspected COVID-19.

OBJECTIVE: To prospectively evaluate a logistic regression-based machine learning (ML) prognostic algorithm implemented in real-time as a clinical dec...

Efficient Approach towards Detection and Identification of Copy Move and Image Splicing Forgeries Using Mask R-CNN with MobileNet V1.

With the technological advancements of the modern era, the easy availability of image editing tools has dramatically minimized the costs, expense, and...

AI Based Monitoring of Different Risk Levels in COVID-19 Context.

COVID-19 was responsible for devastating social, economic, and political effects all over the world. Although the health authorities imposed restricti...

Screening for prostate cancer: a study on the free and total prostate specific antigen.

BACKGROUND: A variety of biomarkers have been developed to monitor growth of cancerous diseases and to detect them at an early stage. Prostate-specifi...

BEMD-3DCNN-based method for COVID-19 detection.

The coronavirus outbreak continues to spread around the world and no one knows when it will stop. Therefore, from the first day of the identification ...

Digital Technology in Diagnostic Breast Pathology and Immunohistochemistry.

Digital technology has been used in the field of diagnostic breast pathology and immunohistochemistry (IHC) for decades. Examples include automated ti...

RegVar: Tissue-specific Prioritization of Non-coding Regulatory Variants.

Non-coding genomic variants constitute the majority of trait-associated genome variations; however, the identification of functional non-coding varian...

A highly accurate delta check method using deep learning for detection of sample mix-up in the clinical laboratory.

OBJECTIVES: Delta check (DC) is widely used for detecting sample mix-up. Owing to the inadequate error detection and high false-positive rate, the imp...

Development of computer-aided model to differentiate COVID-19 from pulmonary edema in lung CT scan: EDECOVID-net.

The efforts made to prevent the spread of COVID-19 face specific challenges in diagnosing COVID-19 patients and differentiating them from patients wit...

Data Homogeneity Effect in Deep Learning-Based Prediction of Type 1 Diabetic Retinopathy.

This study is aimed at evaluating a deep transfer learning-based model for identifying diabetic retinopathy (DR) that was trained using a dataset with...

Comparison of Higher-Than-Standard to D-Dimer Driven Thromboprophylaxis in Hospitalized Patients With COVID-19.

Coronavirus disease 2019 is a global health threat often accompanied with coagulopathy. Despite use of thromboprophylaxis in this population, thrombo...

A Rapid Artificial Intelligence-Based Computer-Aided Diagnosis System for COVID-19 Classification from CT Images.

The excessive number of COVID-19 cases reported worldwide so far, supplemented by a high rate of false alarms in its diagnosis using the conventional ...

Use of machine learning to classify high-risk variants of uncertain significance in lamin A/C cardiac disease.

BACKGROUND: Variation in lamin A/C results in a spectrum of clinical disease, including arrhythmias and cardiomyopathy. Benign variation is rare, and ...

Deep learning reveals personalized spatial spectral abnormalities of high delta and low alpha bands in EEG of patients with early Parkinson's disease.

Parkinson's disease (PD) is one of the most common neurodegenerative diseases, and early diagnosis is crucial to delay disease progression. The diagno...

DNA-based artificial dendritic cells for in situ cytotoxic T cell stimulation and immunotherapy.

In immunotherapy, ex vivo stimulation of T cells requires significant resources and effort. Here, we report artificial dendritic cell-mimicking DNA mi...

A Preliminary Investigation on the Antiviral Activities of the Philippine Marshmint (Mentha arvensis) Leaf Extracts against Dengue Virus Serotype 2 In Vitro.

In this study, we investigated the antiviral activity of lyophilized crude leaf extracts of the Philippine marshmint (Mentha arvensis L., commonly cal...