Infectious Disease

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility.

antibiotic susceptibility testing often fails to accurately predict drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia coli K-12 MG1655 as contextualized through machine le...

Emergent antibacterial activity of -(thiazol-2-yl)benzenesulfonamides in conjunction with cell-penetrating octaarginine.

Hybrid antimicrobials that combine the effect of two or more agents represent a promising antibacterial therapeutic strategy. In this work, we have synthesized -(4-(4-(methylsulfonyl)phenyl)-5-phenylthiazol-2-yl)benzenesulfonamide derivatives that combine thiazole and sulfonamide, groups with known antibacterial activity. These molecules are investigated for their antibacterial activity, in isolat...

Plasmonic Fiberoptic Absorbance Biosensor (P-FAB) for Rapid Detection of SARS-CoV-2 Nucleocapsid Protein.

SARS-CoV-2 nucleocapsid protein-based COVID-19 diagnosis is a promising alternative to the high-priced, time-consuming, and labor-intensive RT-PCR tes...

Dengue models based on machine learning techniques: A systematic literature review.

BACKGROUND: Dengue modeling is a research topic that has increased in recent years. Early prediction and decision-making are key factors to control de...

On the Use of Deep Learning for Imaging-Based COVID-19 Detection Using Chest X-rays.

The global COVID-19 pandemic that started in 2019 and created major disruptions around the world demonstrated the imperative need for quick, inexpensi...

Research on Classification of COVID-19 Chest X-Ray Image Modal Feature Fusion Based on Deep Learning.

Most detection methods of coronavirus disease 2019 (COVID-19) use classic image classification models, which have problems of low recognition accuracy...

Explainable Artificial Intelligence for Bias Detection in COVID CT-Scan Classifiers.

PROBLEM: An application of Explainable Artificial Intelligence Methods for COVID CT-Scan classifiers is presented.

Antibacterial and antibiofilm activities of silver-decorated zinc ferrite nanoparticles synthesized by a gamma irradiation-coupled sol-gel method against some pathogenic bacteria from medical operating room surfaces.

This work aimed at the gamma irradiation-assisted synthesis of silver (Ag)-decorated ZnFeO (ZFO) ferrite nanoparticles (NPs), which were tested for th...

X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic.

PURPOSE: Due to the excessive use of raw materials in diagnostic tools and equipment during the COVID-19 pandemic, there is a dire need for cheaper an...

A New Optimal Diagnosis System for Coronavirus (COVID-19) Diagnosis Based on Archimedes Optimization Algorithm on Chest X-Ray Images.

The new coronavirus, COVID-19, has affected people all over the world. Coronaviruses are a large group of viruses that can infect animals and humans a...

Fast identification of off-target liabilities in early antibiotic discovery with Fourier-transform infrared spectroscopy.

Structural modifications of known antibiotic scaffolds have kept the upper hand on resistance, but we are on the verge of not having antibiotics for m...

Estimating the conditional probability of developing human papilloma virus related oropharyngeal cancer by combining machine learning and inverse Bayesian modelling.

The epidemic increase in the incidence of Human Papilloma Virus (HPV) related Oropharyngeal Squamous Cell Carcinomas (OPSCCs) in several countries wor...

Nasopharyngeal metabolomics and machine learning approach for the diagnosis of influenza.

BACKGROUND: Respiratory virus infections are significant causes of morbidity and mortality, and may induce host metabolite alterations by infecting re...

An approach to rapidly assess sepsis through multi-biomarker host response using machine learning algorithm.

Sepsis is a life-threatening condition and understanding the disease pathophysiology through the use of host immune response biomarkers is critical fo...

Classification for avian malaria parasite Plasmodium gallinaceum blood stages by using deep convolutional neural networks.

The infection of an avian malaria parasite (Plasmodium gallinaceum) in domestic chickens presents a major threat to the poultry industry because it ca...

COVID-19 sentiment analysis via deep learning during the rise of novel cases.

Social scientists and psychologists take interest in understanding how people express emotions and sentiments when dealing with catastrophic events su...

Optimal Diagnosis of COVID-19 Based on Convolutional Neural Network and Red Fox Optimization Algorithm.

SARS-CoV-2 is a specific type of Coronavirus that was firstly reported in China in December 2019 and is the causative agent of coronavirus disease 201...

Performance of Fully Automated Antimicrobial Disk Diffusion Susceptibility Testing Using Copan WASP Colibri Coupled to the Radian In-Line Carousel and Expert System.

The purpose of the present study was to assess the agreement at the categorical level between the Vitek 2 system and the Colibri coupled to the Radian...

Natural Language Processing Insight into LGBTQ+ Youth Mental Health During the COVID-19 Pandemic: Longitudinal Content Analysis of Anxiety-Provoking Topics and Trends in Emotion in LGBTeens Microcommunity Subreddit.

BACKGROUND: Widespread fear surrounding COVID-19, coupled with physical and social distancing orders, has caused severe adverse mental health outcomes...

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort.

BACKGROUND: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 pati...