Infectious Disease

An Exploratory Study of a New Vancomycin Eye Drops Formulation for Extemporaneous Compounding.

PURPOSE: Compounded eye drop solutions of vancomycin hydrochloride have important clinical applications, such as postoperative antimicrobial prophylaxis and bacterial keratitis. There exists a plethora of data to support the use of various liquid vehicles to compound vancomycin hydrochloride eye drops. However, there are a number of limitations for implementation, especially the frequent shortage ...

Noninvasive diagnostic of periprosthetic joint infection by urinary peptide markers: A preliminary study.

Previous immunohistochemical analyses revealed altered protein expression in the periprosthetic membranes of patients with periprosthetic joint infection (PJI). Proteins are degraded to peptides that may pass the blood-kidney barrier depending on their size. The aim of this study was to evaluate if PJI can be diagnosed based on the urinary peptide excretion pattern. Thirty patients undergoing remo...

Intractable airsickness associated with COVID-19: A case report.

A 29-yr-old male Melicopter co-pilot with high flight hours in air transport missions of the patients with COVID-19 tested positive for his RT-PCR due...

Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach.

BACKGROUND: It is important to measure the public response to the COVID-19 pandemic. Twitter is an important data source for infodemiology studies inv...

Machine-learning classification of texture features of portable chest X-ray accurately classifies COVID-19 lung infection.

BACKGROUND: The large volume and suboptimal image quality of portable chest X-rays (CXRs) as a result of the COVID-19 pandemic could post significant ...

DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large U.S. Clinical Data Set.

Background There are characteristic findings of coronavirus disease 2019 (COVID-19) on chest images. An artificial intelligence (AI) algorithm to dete...

The Potential of Artificial Intelligence to Analyze Chest Radiographs for Signs of COVID-19 Pneumonia.

Design and rationale of an intelligent algorithm to detect BuRnoUt in HeaLthcare workers in COVID era using ECG and artificiaL intelligence: The BRUCEE-LI study.

BACKGROUND: There is no large contemporary data from India to see the prevalence of burnout in HCWs in covid era. Burnout and mental stress is associa...

Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools.

The outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune res...

Pre-Trained Deep Convolutional Neural Network for Clostridioides Difficile Bacteria Cytotoxicity Classification Based on Fluorescence Images.

infection (CDI) is an enteric bacterial disease that is increasing in incidence worldwide. Symptoms of CDI range from mild diarrhea to severe life-th...

Internet of Medical Things: An Effective and Fully Automatic IoT Approach Using Deep Learning and Fine-Tuning to Lung CT Segmentation.

Several pathologies have a direct impact on society, causing public health problems. Pulmonary diseases such as Chronic obstructive pulmonary disease ...

Deep-learning algorithms for the interpretation of chest radiographs to aid in the triage of COVID-19 patients: A multicenter retrospective study.

The recent medical applications of deep-learning (DL) algorithms have demonstrated their clinical efficacy in improving speed and accuracy of image in...

Mobile Health (mHealth) Viral Diagnostics Enabled with Adaptive Adversarial Learning.

Deep-learning (DL)-based image processing has potential to revolutionize the use of smartphones in mobile health (mHealth) diagnostics of infectious d...

Performance evaluation of machine learning-based infectious screening flags on the HORIBA Medical Yumizen H550 Haematology Analyzer for vivax malaria and dengue fever.

BACKGROUND: Automated detection of malaria and dengue infection has been actively researched for more than two decades. Although many improvements hav...

Virtual screening of anti-HIV1 compounds against SARS-CoV-2: machine learning modeling, chemoinformatics and molecular dynamics simulation based analysis.

COVID-19 caused by the SARS-CoV-2 is a current global challenge and urgent discovery of potential drugs to combat this pandemic is a need of the hour....

Application of artificial neural networks to predict the COVID-19 outbreak.

BACKGROUND: Millions of people have been infected worldwide in the COVID-19 pandemic. In this study, we aim to propose fourteen prediction models base...

Exploiting Multiple Optimizers with Transfer Learning Techniques for the Identification of COVID-19 Patients.

Due to the rapid spread of COVID-19 and its induced death worldwide, it is imperative to develop a reliable tool for the early detection of this disea...

Machine Learning Approaches Reveal That the Number of Tests Do Not Matter to the Prediction of Global Confirmed COVID-19 Cases.

Coronavirus disease 2019 (COVID-19) has developed into a global pandemic, affecting every nation and territory in the world. Machine learning-based ap...

Early survey with bibliometric analysis on machine learning approaches in controlling COVID-19 outbreaks.

BACKGROUND AND OBJECTIVE: The COVID-19 pandemic has caused severe mortality across the globe, with the USA as the current epicenter of the COVID-19 ep...

Mitigating Biases in CORD-19 for Analyzing COVID-19 Literature.

On the behest of the Office of Science and Technology Policy in the White House, six institutions, including ours, have created an open research datas...