Infectious Disease

Classification of COVID-19 electrocardiograms by using hexaxial feature mapping and deep learning.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a pandemic since its first appearance in late 2019. Deaths caused by COVID-19 are still increasing day by day and early diagnosis has become crucial. Since current diagnostic methods have many disadvantages, new investigations are needed to improve the performance of diagnosis.

Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2.

A global pandemic has emerged following the appearance of the new severe acute respiratory virus whose official name is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strongly affecting the health sector as well as the world economy. Indeed, following the emergence of this new virus, despite the existence of a few approved and known effective vaccines at the time of writing this...

Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19.

BACKGROUND AND OBJECTIVES: AKI treated with dialysis initiation is a common complication of coronavirus disease 2019 (COVID-19) among hospitalized pat...

COVID-19 diagnosis by routine blood tests using machine learning.

Physicians taking care of patients with COVID-19 have described different changes in routine blood parameters. However, these changes hinder them from...

Predicting Prolonged Hospitalization and Supplemental Oxygenation in Patients with COVID-19 Infection from Ambulatory Chest Radiographs using Deep Learning.

RATIONALE AND OBJECTIVES: The clinical prognosis of outpatients with coronavirus disease 2019 (COVID-19) remains difficult to predict, with outcomes i...

A COVID-19 Pandemic Artificial Intelligence-Based System With Deep Learning Forecasting and Automatic Statistical Data Acquisition: Development and Implementation Study.

BACKGROUND: More than 79.2 million confirmed COVID-19 cases and 1.7 million deaths were caused by SARS-CoV-2; the disease was named COVID-19 by the Wo...

Segmenting lung lesions of COVID-19 from CT images via pyramid pooling improved Unet.

Segmenting lesion regions of Coronavirus Disease 2019 (COVID-19) from computed tomography (CT) images is a challenge owing to COVID-19 lesions charact...

Kinematics approach with neural networks for early detection of sepsis (KANNEDS).

BACKGROUND: Sepsis is a severe illness that affects millions of people worldwide, and its early detection is critical for effective treatment outcomes...

COVID-19 and the kidney: A retrospective analysis of 37 critically ill patients using machine learning.

INTRODUCTION: There is evidence that SARS-CoV2 has a particular affinity for kidney tissue and is often associated with kidney failure.

Specificity of SARS-CoV-2 Real-Time PCR Improved by Deep Learning Analysis.

Real-time PCR (RT-PCR) is widely used to diagnose human pathogens. RT-PCR data are traditionally analyzed by estimating the threshold cycle ( ) at whi...

Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis.

BACKGROUND: COVID-19 is one of the greatest threats to human beings in terms of health care, economy, and society in recent history. Up to this moment...

Prediction of population behavior of Listeria monocytogenes in food using machine learning and a microbial growth and survival database.

In predictive microbiology, statistical models are employed to predict bacterial population behavior in food using environmental factors such as tempe...

Rational structural modification of the isatin scaffold to develop new and potent antimicrobial agents targeting bacterial peptidoglycan glycosyltransferase.

A series of isatin derivatives bearing three different substituent groups at the N-1, C-3 and C-5 positions of the isatin scaffold were systematically...

Influenza forecasting for French regions combining EHR, web and climatic data sources with a machine learning ensemble approach.

Effective and timely disease surveillance systems have the potential to help public health officials design interventions to mitigate the effects of d...

Understanding Public Perceptions of COVID-19 Contact Tracing Apps: Artificial Intelligence-Enabled Social Media Analysis.

BACKGROUND: The emergence of SARS-CoV-2 in late 2019 and its subsequent spread worldwide continues to be a global health crisis. Many governments cons...

Comparison of machine-learning methodologies for accurate diagnosis of sepsis using microarray gene expression data.

We investigate the feasibility of molecular-level sample classification of sepsis using microarray gene expression data merged by in silico meta-analy...

Generative Adversarial Networks for Creating Synthetic Free-Text Medical Data: A Proposal for Collaborative Research and Re-use of Machine Learning Models.

Restrictions in sharing Patient Health Identifiers (PHI) limit cross-organizational re-use of free-text medical data. We leverage Generative Adversari...

ESUR/ESUI position paper: developing artificial intelligence for precision diagnosis of prostate cancer using magnetic resonance imaging.

Artificial intelligence developments are essential to the successful deployment of community-wide, MRI-driven prostate cancer diagnosis. AI systems sh...

Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic.

The advancement of technology remained an immersive interest for humankind throughout the past decades. Tech enterprises offered a stream of innovatio...

Effects of gait training with a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), on quality of life in patients with neuromuscular disease, able to walk independently with aids.

Robot-assisted gait training using a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), has been shown to improve the mobility of patients...