Infectious Disease

Detection of COVID-19 from Chest X-ray Images Using Deep Convolutional Neural Networks.

The COVID-19 global pandemic has wreaked havoc on every aspect of our lives. More specifically, healthcare systems were greatly stretched to their limits and beyond. Advances in artificial intelligence have enabled the implementation of sophisticated applications that can meet clinical accuracy requirements. In this study, customized and pre-trained deep learning models based on convolutional neur...

Chlorinated metabolites with antibacterial activities from a deep-sea-derived fungus.

Chromatographic separation of the solid cultures of a deep-sea-derived fungus (MCCC 3A00308) resulted in the isolation of eight compounds. Their structures were identified on the basis of the spectroscopic data. Compounds 1-8 are classified as depsidone-type (1-4), isocoumarin-type (5 and 6), and benzothiazole-type (7 and 8), of which 1-7 are new compounds and 1-3 along with 5 and 6 are chlorinat...

Helminth egg analysis platform (HEAP): An opened platform for microscopic helminth egg identification and quantification based on the integration of deep learning architectures.

BACKGROUND: Millions of people throughout the world suffer from parasite infections. Traditionally, technicians use manual eye inspection of microscop...

Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective.

Artificial intelligence (AI) applications for chest radiography and chest CT are among the most developed applications in radiology. More than 40 cert...

Delivery mode and perinatal antibiotics influence the predicted metabolic pathways of the gut microbiome.

Delivery mode and perinatal antibiotics influence gut microbiome composition in children. Most microbiome studies have used the sequencing of the bact...

Vaso reactivity test using inhaled nitric oxide for pulmonary arterial hypertension accompanied by severe interstitial lung disease attributed to systemic sclerosis: A case report.

A 70-year-old man with severe interstitial pneumonia attributed to limited cutaneous systemic sclerosis was referred to our institution because of wor...

Accurate diagnosis of sepsis using a neural network: Pilot study using routine clinical variables.

BACKGROUND AND OBJECTIVES: Sepsis is a severe infection that increases mortality risk and is one if the main causes of death in intensive care units. ...

Medical-VLBERT: Medical Visual Language BERT for COVID-19 CT Report Generation With Alternate Learning.

Medical imaging technologies, including computed tomography (CT) or chest X-Ray (CXR), are largely employed to facilitate the diagnosis of the COVID-1...

Recognition of COVID-19 from CT Scans Using Two-Stage Deep-Learning-Based Approach: CNR-IEMN.

Since the appearance of the COVID-19 pandemic (at the end of 2019, Wuhan, China), the recognition of COVID-19 with medical imaging has become an activ...

Synthesis of covalent bonding MWCNT-oligoethylene linezolid conjugates and their antibacterial activity against bacterial strains.

Nowadays, infectious diseases caused by drug-resistant bacteria have become especially important. Linezolid is an antibacterial drug active against cl...

Physically crosslinked PVA/graphene-based materials/aloe vera hydrogel with antibacterial activity.

Burn is a major skin injury that occurs worldwide. For second-degree burns, special treatment should be given for creating a suitable wound healing en...

GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning.

BACKGROUND: Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mt...

Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset.

The COVID-19 outbreak began in December 2019 and has dreadfully affected our lives since then. More than three million lives have been engulfed by thi...

Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases.

In the era of antimicrobial resistance, the prevalence of multidrug-resistant microorganisms that resist conventional antibiotic treatment has steadil...

Hybrid COVID-19 segmentation and recognition framework (HMB-HCF) using deep learning and genetic algorithms.

COVID-19 (Coronavirus) went through a rapid escalation until it became a pandemic disease. The normal and manual medical infection discovery may take ...

CIDO ontology updates and secondary analysis of host responses to COVID-19 infection based on ImmPort reports and literature.

BACKGROUND: With COVID-19 still in its pandemic stage, extensive research has generated increasing amounts of data and knowledge. As many studies are ...

Automated description of the mandible shape by deep learning.

PURPOSE: The shape of the mandible has been analyzed in a variety of fields, whether to diagnose conditions like osteoporosis or osteomyelitis, in for...

Artificial Intelligence Predicts Severity of COVID-19 Based on Correlation of Exaggerated Monocyte Activation, Excessive Organ Damage and Hyperinflammatory Syndrome: A Prospective Clinical Study.

BACKGROUND: Prediction of the severity of COVID-19 at its onset is important for providing adequate and timely management to reduce mortality.

Benzo[]thiazole-2-thiol bearing 2-oxo-2-substituted-phenylethan-1-yl as potent selective quorum sensing inhibitors of Gram-negative bacteria.

Quorum sensing is a well-known term for describing bacterial cell-cell communication. Bacteria use quorum sensing pathways to respond to external fact...

Using machine learning and big data to explore the drug resistance landscape in HIV.

Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitted to naive patients. The standard approach to rev...