Universal precautions

Exploration of text matching methods in Chinese disease Q&A systems: A method using ensemble based on BERT and boosted tree models.

BACKGROUND: Text matching is one of the basic tasks in the field of natural language processing. Owing to the particularity of Chinese language and medical texts, text matching has greater application and research value in the medical field. In 2019, at the China Health Information Processing Conference (CHIP), 30,000 sets of real disease Q&A data in Chinese on diabetes, hypertension, hepatitis B,...

Machine learning prediction of neurocognitive impairment among people with HIV using clinical and multimodal magnetic resonance imaging data.

Diagnosis of HIV-associated neurocognitive impairment (NCI) continues to be a clinical challenge. The purpose of this study was to develop a prediction model for NCI among people with HIV using clinical- and magnetic resonance imaging (MRI)-derived features. The sample included 101 adults with chronic HIV disease. NCI was determined using a standardized neuropsychological testing battery comprised...

A dual-task dual-domain model for blind MRI reconstruction.

MRI reconstruction is the key technology to accelerate MR acquisition. Recent cascade models have gained satisfactory results, however, they deeply re...

A deep learning approach to the screening of malaria infection: Automated and rapid cell counting, object detection and instance segmentation using Mask R-CNN.

Accurate and early diagnosis is critical to proper malaria treatment and hence death prevention. Several computer vision technologies have emerged in ...

Multi disease-prediction framework using hybrid deep learning: an optimal prediction model.

Big data and its approaches are generally helpful for healthcare and biomedical sectors for predicting the disease. For trivial symptoms, the difficul...

iT3SE-PX: Identification of Bacterial Type III Secreted Effectors Using PSSM Profiles and XGBoost Feature Selection.

Identification of bacterial type III secreted effectors (T3SEs) has become a popular research topic in the field of bioinformatics due to its crucial ...

Mask R-CNN and OBIA Fusion Improves the Segmentation of Scattered Vegetation in Very High-Resolution Optical Sensors.

Vegetation generally appears scattered in drylands. Its structure, composition and spatial patterns are key controls of biotic interactions, water, an...

Integrated meta-analysis and machine learning approach identifies acyl-CoA thioesterase with other novel genes responsible for biofilm development in Staphylococcus aureus.

Biofilm forming Staphylococcus aureus is a major threat to the health-care industry. It is important to understand the differences between planktonic ...

The role of quantitative HBsAg in the natural history of e antigen-negative chronic hepatitis B: A Tunisian prospective study.

BACKGROUND/AIMS: During the natural course of Chronic Hepatitis B (CHB) infection, differentiation between inactive carrier (IC) and HBeAg negative CH...

Evolution of drug resistance in HIV protease.

BACKGROUND: Drug resistance is a critical problem limiting effective antiviral therapy for HIV/AIDS. Computational techniques for predicting drug resi...

Clinical Case Report: Dissociation of Clinical Course of Coexisting Autoimmune Hepatitis and Graves Disease.

OBJECTIVE: Concurrent autoimmune disorders, including autoimmune hepatitis (AIH), with Graves disease have been reported. Glucocorticoids can simultan...

The Prediction of Hepatitis E through Ensemble Learning.

According to the World Health Organization, about 20 million people are infected with Hepatitis E every year. In 2015, there were 44,000 deaths due to...

Repurposing potential of FDA-approved and investigational drugs for COVID-19 targeting SARS-CoV-2 spike and main protease and validation by machine learning algorithm.

The present study aimed to assess the repurposing potential of existing antiviral drug candidates (FDA-approved and investigational) against SARS-CoV-...

Semi-automatic sigmoid colon segmentation in CT for radiation therapy treatment planning via an iterative 2.5-D deep learning approach.

Automatic sigmoid colon segmentation in CT for radiotherapy treatment planning is challenging due to complex organ shape, close distances to other org...

Quality control, HPTLC analysis, antioxidant and antimicrobial activity of hydroalcoholic extract of roots of ( C.B Clarke).

OBJECTIVES: , CB Clarke () is a perennial herb of the Compositae family. The root of has been used for the treatment of various diseases such as hepa...

Hepatitis C viral load and genotypes among Nigerian subjects with chronic infection and implication for patient management: a retrospective review of data.

INTRODUCTION: Hepatitis C Virus (HCV) is highly infectious with no currently available vaccine. Prior to treatment, it is recommended to confirm HCV i...

Accurate spatiotemporal mapping of drug overdose deaths by machine learning of drug-related web-searches.

Persons who inject drugs (PWID) are at increased risk for overdose death (ODD), infections with HIV, hepatitis B (HBV) and hepatitis C virus (HCV), an...

Post-DAE: Anatomically Plausible Segmentation via Post-Processing With Denoising Autoencoders.

We introduce Post-DAE, a post-processing method based on denoising autoencoders (DAE) to improve the anatomical plausibility of arbitrary biomedical i...

Predicted Cellular Immunity Population Coverage Gaps for SARS-CoV-2 Subunit Vaccines and Their Augmentation by Compact Peptide Sets.

Subunit vaccines induce immunity to a pathogen by presenting a component of the pathogen and thus inherently limit the representation of pathogen pept...

Training confounder-free deep learning models for medical applications.

The presence of confounding effects (or biases) is one of the most critical challenges in using deep learning to advance discovery in medical imaging ...