COVID-19

COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images.

Chest-X ray (CXR) radiography can be used as a first-line triage process for non-COVID-19 patients with pneumonia. However, the similarity between features of CXR images of COVID-19 and pneumonia caused by other infections makes the differential diagnosis by radiologists challenging. We hypothesized that machine learning-based classifiers can reliably distinguish the CXR images of COVID-19 patient...

Texture analysis of muscle MRI: machine learning-based classifications in idiopathic inflammatory myopathies.

To develop a machine learning (ML) model that predicts disease groups or autoantibodies in patients with idiopathic inflammatory myopathies (IIMs) using muscle MRI radiomics features. Twenty-two patients with dermatomyositis (DM), 14 with amyopathic dermatomyositis (ADM), 19 with polymyositis (PM) and 19 with non-IIM were enrolled. Using 2D manual segmentation, 93 original features as well as 93 l...

Predicting mean ribosome load for 5'UTR of any length using deep learning.

The 5' untranslated region plays a key role in regulating mRNA translation and consequently protein abundance. Therefore, accurate modeling of 5'UTR r...

Gene selection using hybrid dragonfly black hole algorithm: A case study on RNA-seq COVID-19 data.

This paper introduces a new hybrid approach (DBH) for solving gene selection problem that incorporates the strengths of two existing metaheuristics: b...

ai-corona: Radiologist-assistant deep learning framework for COVID-19 diagnosis in chest CT scans.

The development of medical assisting tools based on artificial intelligence advances is essential in the global fight against COVID-19 outbreak and th...

Conjunctival Provocation Test With .

Conjunctival provocation test (CPT) is used to demonstrate clinical relevance to a specific allergen. (Bt) is a prevalent allergen in tropical regio...

Automated accurate emotion recognition system using rhythm-specific deep convolutional neural network technique with multi-channel EEG signals.

Emotion is interpreted as a psycho-physiological process, and it is associated with personality, behavior, motivation, and character of a person. The ...

A comprehensive review and analysis of supervised-learning and soft computing techniques for stress diagnosis in humans.

Stress is the most prevailing and global psychological condition that inevitably disrupts the mood and behavior of individuals. Chronic stress may gra...

Adjuvant Therapy System of COVID-19 Patient: Integrating Warning, Therapy, Post-Therapy Psychological Intervention.

The 2019 novel coronavirus(COVID-19) spreads rapidly, and the large-scale infection leads to the lack of medical resources. For the purpose of providi...

A frogspawn-like Ag@C core-shell structure for an ultrasensitive label-free electrochemical immunosensing of carcinoembryonic antigen in blood plasma.

A three-dimensional (3D) frogspawn-like structure was achieved by simply coating nano-carbon outside silver nanospheres (Ag@C NFS) and used as a probe...

Efficient Automated Disease Diagnosis Using Machine Learning Models.

Recently, many researchers have designed various automated diagnosis models using various supervised learning models. An early diagnosis of disease ma...

Convolutional Sparse Support Estimator-Based COVID-19 Recognition From X-Ray Images.

Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessi...

Pseudocell Tracer-A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombination.

Single cell RNA sequencing (scRNAseq) can be used to infer a temporal ordering of cellular states. Current methods for the inference of cellular traje...

Automated Diagnosis of COVID-19 Using Deep Features and Parameter Free BAT Optimization.

Accurate and fast diagnosis of COVID-19 is very important to manage the medical conditions of affected persons. The task is challenging owing to shor...

FBSED based automatic diagnosis of COVID-19 using X-ray and CT images.

This work introduces the Fourier-Bessel series expansion-based decomposition (FBSED) method, which is an implementation of the wavelet packet decompos...

NIA-Network: Towards improving lung CT infection detection for COVID-19 diagnosis.

During pandemics (e.g., COVID-19) physicians have to focus on diagnosing and treating patients, which often results in that only a limited amount of l...

LBP-based information assisted intelligent system for COVID-19 identification.

A real-time COVID-19 detection system is an utmost requirement of the present situation. This article presents a chest X-ray image-based automated COV...

Interpreting deep learning models for epileptic seizure detection on EEG signals.

While Deep Learning (DL) is often considered the state-of-the art for Artificial Intel-ligence-based medical decision support, it remains sparsely imp...

A minimal model of the interaction of social and individual learning.

Learning is thought to be achieved by the selective, activity dependent, adjustment of synaptic connections. Individual learning can also be very hard...

Classification of COVID-19 chest X-Ray and CT images using a type of dynamic CNN modification method.

Understanding and classifying Chest X-Ray (CXR) and computerised tomography (CT) images are of great significance for COVID-19 diagnosis. The existing...