COVID-19

The study of automatic machine learning base on radiomics of non-focus area in the first chest CT of different clinical types of COVID-19 pneumonia.

To explore the possibility of predicting the clinical types of Corona-Virus-Disease-2019 (COVID-19) pneumonia by analyzing the non-focus area of the lung in the first chest CT image of patients with COVID-19 by using automatic machine learning (Auto-ML). 136 moderate and 83 severe patients were selected from the patients with COVID-19 pneumonia. The clinical and laboratory data were collected for ...

Prototype Development of an Expert System of Computerized Clinical Guidelines for COVID-19 Diagnosis and Management in Saudi Arabia.

The increasing number of COVID-19 patients has increased health care professionals' workloads, making the management of dynamic patient information in a timely and comprehensive manner difficult and sometimes impossible. Compounding this problem is a lack of health care professionals and trained medical staff to handle the increased number of patients. Although Saudi Arabia has recently improved t...

The importance of standardisation - COVID-19 CT & Radiograph Image Data Stock for deep learning purpose.

With the number of affected individuals still growing world-wide, the research on COVID-19 is continuously expanding. The deep learning community conc...

PharmGKB Tutorial for Pharmacogenomics of Drugs Potentially Used in the Context of COVID-19.

Pharmacogenomics (PGx) is a key area of precision medicine, which is already being implemented in some health systems and may help guide clinicians to...

Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures.

PURPOSE: High-dimensional image features that underlie COVID-19 pneumonia remain opaque. We aim to compare feature engineering and deep learning metho...

Implementation of convolutional neural network approach for COVID-19 disease detection.

In this paper, two novel, powerful, and robust convolutional neural network (CNN) architectures are designed and proposed for two different classifica...

Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests.

OBJECTIVES: The rRT-PCR test, the current gold standard for the detection of coronavirus disease (COVID-19), presents with known shortcomings, such as...

Digital Twin Coaching for Physical Activities: A Survey.

Digital Twin technology has been rising in popularity thanks to the popularity of machine learning in the last decade. As the life expectancy of peopl...

A Comprehensive Analysis of MicroRNAs in Human Osteoporosis.

MicroRNAs (miRNAs) are single-stranded RNA molecules that control gene expression in various processes, such as cancers, Alzheimer's disease, and bone...

AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia.

Coronavirus disease 2019 (COVID-19) emerged in 2019 and disseminated around the world rapidly. Computed tomography (CT) imaging has been proven to be ...

Continuous Infusion Low-Dose Unfractionated Heparin for the Management of Hypercoagulability Associated With COVID-19.

INTRODUCTION: The Coronavirus Disease 2019 (COVID-19) is associated with severe hypercoagulability. There is currently limited evidence supporting the...

UVC disinfection robot.

The aim of the present work is to contribute in the fight against the spread of Covid-19, a novel human coronavirus, in hospitals, public transport, a...

Automatic multi-needle localization in ultrasound images using large margin mask RCNN for ultrasound-guided prostate brachytherapy.

Multi-needle localization in ultrasound (US) images is a crucial step of treatment planning for US-guided prostate brachytherapy. However, current com...

Development and evaluation of an artificial intelligence system for COVID-19 diagnosis.

Early detection of COVID-19 based on chest CT enables timely treatment of patients and helps control the spread of the disease. We proposed an artific...

A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks.

The use of imaging data has been reported to be useful for rapid diagnosis of COVID-19. Although computed tomography (CT) scans show a variety of sign...

Large-Scale Multi-omic Analysis of COVID-19 Severity.

We performed RNA-seq and high-resolution mass spectrometry on 128 blood samples from COVID-19-positive and COVID-19-negative patients with diverse dis...

Dual-branch combination network (DCN): Towards accurate diagnosis and lesion segmentation of COVID-19 using CT images.

The recent global outbreak and spread of coronavirus disease (COVID-19) makes it an imperative to develop accurate and efficient diagnostic tools for ...

MRI-based machine learning radiomics can predict HER2 expression level and pathologic response after neoadjuvant therapy in HER2 overexpressing breast cancer.

BACKGROUND: To use clinical and MRI radiomic features coupled with machine learning to assess HER2 expression level and predict pathologic response (p...

Biomechanically constrained non-rigid MR-TRUS prostate registration using deep learning based 3D point cloud matching.

A non-rigid MR-TRUS image registration framework is proposed for prostate interventions. The registration framework consists of a convolutional neural...

Issues associated with deploying CNN transfer learning to detect COVID-19 from chest X-rays.

Covid-19 first occurred in Wuhan, China in December 2019. Subsequently, the virus spread throughout the world and as of June 2020 the total number of ...