Universal precautions

Investigation of the effectiveness of a classification method based on improved DAE feature extraction for hepatitis C prediction.

Hepatitis C, a particularly dangerous form of viral hepatitis caused by hepatitis C virus (HCV) infection, is a major socio-economic and public health problem. Due to the rapid development of deep learning, it has become a common practice to apply deep learning to the healthcare industry to improve the effectiveness and accuracy of disease identification. In order to improve the effectiveness and ...

Molecular Docking Improved with Human Spatial Perception Using Virtual Reality.

Adaptive steered molecular dynamics (ASMD) is a computational biophysics method in which an external force is applied to a selected set of atoms or a specific reaction coordinate to induce a particular molecular motion. Virtual reality (VR) based methods for protein-ligand docking are beneficial for visualizing on-the-fly interactive molecular dynamics and performing promising docking trajectories...

Machine-Learning-Assisted Aggregation-Induced Emissive Nanosilicon-Based Sensor Array for Point-of-Care Identification of Multiple Foodborne Pathogens.

How timely identification and determination of pathogen species in pathogen-contaminated foods are responsible for rapid and accurate treatments for f...

An artificial intelligence-generated model predicts 90-day survival in alcohol-associated hepatitis: A global cohort study.

BACKGROUND AND AIMS: Alcohol-associated hepatitis (AH) poses significant short-term mortality. Existing prognostic models lack precision for 90-day mo...

Dilated Heterogeneous Convolution for Cell Detection and Segmentation Based on Mask R-CNN.

Owing to the variable shapes, large size difference, uneven grayscale, and dense distribution among biological cells in an image, it is very difficult...

Deep learning-based image annotation for leukocyte segmentation and classification of blood cell morphology.

The research focuses on the segmentation and classification of leukocytes, a crucial task in medical image analysis for diagnosing various diseases. T...

Early gastric cancer detection and lesion segmentation based on deep learning and gastroscopic images.

Gastric cancer is a highly prevalent disease that poses a serious threat to public health. In clinical practice, gastroscopy is frequently used by med...

Deep learning workflow to support in-flight processing of digital aerial imagery for wildlife population surveys.

Deep learning shows promise for automating detection and classification of wildlife from digital aerial imagery to support cost-efficient remote sensi...

Incorporating Machine Learning Strategies to Smart Gloves Enabled by Dual-Network Hydrogels for Multitask Control and User Identification.

Smart gloves are often used in human-computer interaction scenarios due to their portability and ease of integration. However, their application in th...

AI-assisted HIV case finding in Ukraine.

Development and validation of a random forest algorithm for source attribution of animal and human Typhimurium and monophasic variants of Typhimurium isolates in England and Wales utilising whole genome sequencing data.

Source attribution has traditionally involved combining epidemiological data with different pathogen characterisation methods, including 7-gene multi ...

Deep Learning for Face Detection and Pain Assessment in Japanese macaques ().

Facial expressions have increasingly been used to assess emotional states in mammals. The recognition of pain in research animals is essential for the...

A Novel Data Augmentation Approach Using Mask Encoding for Deep Learning-Based Asynchronous SSVEP-BCI.

Deep learning (DL)-based methods have been successfully employed as asynchronous classification algorithms in the steady-state visual evoked potential...

Raman spectrum combined with deep learning for precise recognition of Carbapenem-resistant Enterobacteriaceae.

Carbapenem-resistant Enterobacteriaceae (CRE) is a major pathogen that poses a serious threat to human health. Unfortunately, currently, there are no ...

Retrospective survey of using a novel validated real-time PCR assay.

, an aggressive plant pathogen, causes symptoms on a variety of crops and ornamental plants including bleeding canker of Asian pear trees. Historical ...

Deep learning for automatic detection of cephalometric landmarks on lateral cephalometric radiographs using the Mask Region-based Convolutional Neural Network: a pilot study.

OBJECTIVE: We examined the effectiveness and feasibility of the Mask Region-based Convolutional Neural Network (Mask R-CNN) for automatic detection of...

Study of helminth eggs ( inactivation by anaerobic digestion and electrochemical treatment.

BACKGROUND: The use of insufficiently treated wastewater or Faecal sludge in agriculture raises concerns because of the pathogen content. Helminth egg...

Toward the novel AI tasks in infection biology.

Machine learning and artificial intelligence (AI) are becoming more common in infection biology laboratories around the world. Yet, as they gain tract...

identification of human microRNAs pointing centrin genes in : Considering the RNAi-mediated gene control.

Leishmaniasis, a parasitic disease caused by different species of the protozoa parasite , is a neglected tropical human disease that is endemic in abo...

The Intersections of COVID-19, HIV, and Race/Ethnicity: Machine Learning Methods to Identify and Model Risk Factors for Severe COVID-19 in a Large U.S. National Dataset.

We investigate risk factors for severe COVID-19 in persons living with HIV (PWH), including among racialized PWH, using the U.S. population-sampled Na...