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Universal precautions

Latest AI and machine learning research in universal precautions for healthcare professionals.

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Dermoscopic Features of Giant Molluscum Contagiosum in a Patient with Acquired Immunodeficiency Syndrome.

Giant molluscum contagiosum (MC) is a peculiar variant of the disease with the presence of multiple ...

[Prevalence of transmitted drug resistance in HIV-infected treatment-naive patients in Chile].

BACKGROUND: Transmitted drug resistance (TDR) occurs in patients with HIV infection who are not expo...

Development a hydrolysis probe-based quantitative PCR assay for the specific detection and quantification of .

BACKGROUND AND PURPOSE: is an emerging multidrug-resistant pathogen. The identification of this spe...

'I'm over the moon!': patient-perceived outcomes of hepatitis C treatment.

Understanding patient-perceived outcomes is crucial for assessing the effectiveness and acceptabilit...

Machine Learning Analysis Reveals Novel Neuroimaging and Clinical Signatures of Frailty in HIV.

BACKGROUND: Frailty is an important clinical concern for the aging population of people living with ...

Systematic analysis of supervised machine learning as an effective approach to predicate β-lactam resistance phenotype in Streptococcus pneumoniae.

Streptococcus pneumoniae is the most common human respiratory pathogen, and β-lactam antibiotics hav...

Assisting the Non-invasive Diagnosis of Liver Fibrosis Stages using Machine Learning Methods.

Fibrosis is a significant indication of chronic liver diseases often due to hepatitis C Virus. It is...

Y-Net for Chest X-Ray Preprocessing: Simultaneous Classification of Geometry and Segmentation of Annotations.

Over the last decade, convolutional neural networks (CNNs) have emerged as the leading algorithms in...

Using Machine Learning Algorithms to Predict Antimicrobial Resistance and Assist Empirical Treatment.

Multi-drug-resistant (MDR) infections and their devastating consequences constitute a global problem...

Artificial Intelligence and Machine Learning for HIV Prevention: Emerging Approaches to Ending the Epidemic.

PURPOSE OF REVIEW: We review applications of artificial intelligence (AI), including machine learnin...

Machine-learning classification of neurocognitive performance in children with perinatal HIV initiating de novo antiretroviral therapy.

OBJECTIVE: To develop a predictive model of neurocognitive trajectories in children with perinatal H...

A Bayesian classification model for discriminating common infectious diseases in Zhejiang province, China.

To develop a classification model for accurately discriminating common infectious diseases in Zhejia...

Systems and Precision Medicine in Necrotizing Soft Tissue Infections.

Necrotizing soft tissue infections (NSTI) are multifactorial and characterized by dysfunctional, tim...

PathFlowAI: A High-Throughput Workflow for Preprocessing, Deep Learning and Interpretation in Digital Pathology.

The diagnosis of disease often requires analysis of a biopsy. Many diagnoses depend not only on the ...

DeePaC: predicting pathogenic potential of novel DNA with reverse-complement neural networks.

MOTIVATION: We expect novel pathogens to arise due to their fast-paced evolution, and new species to...

Deep Learning Analysis of Cerebral Blood Flow to Identify Cognitive Impairment and Frailty in Persons Living With HIV.

BACKGROUND: Deep learning algorithms of cerebral blood flow were used to classify cognitive impairme...

SPRINT-Gly: predicting N- and O-linked glycosylation sites of human and mouse proteins by using sequence and predicted structural properties.

MOTIVATION: Protein glycosylation is one of the most abundant post-translational modifications that ...

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