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Universal precautions

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

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Attention-Based Temporal Encoding Network with Background-Independent Motion Mask for Action Recognition.

Convolutional neural network (CNN) has been leaping forward in recent years. However, the high dimen...

Mask-Guided Attention Network and Occlusion-Sensitive Hard Example Mining for Occluded Pedestrian Detection.

Pedestrian detection relying on deep convolution neural networks has made significant progress. Thou...

Unveiling social distancing mechanisms via a fish-robot hybrid interaction.

Pathogen transmission is a major limit of social species. Social distancing, a behavioural-based res...

Machine Learning Prediction and Experimental Validation of Antigenic Drift in H3 Influenza A Viruses in Swine.

The antigenic diversity of influenza A viruses (IAV) circulating in swine challenges the development...

DeepVISP: Deep Learning for Virus Site Integration Prediction and Motif Discovery.

Approximately 15% of human cancers are estimated to be attributed to viruses. Virus sequences can be...

Machine-learning model led design to experimentally test species thermal limits: The case of kissing bugs (Triatominae).

Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic a...

Research perspectives on animal health in the era of artificial intelligence.

Leveraging artificial intelligence (AI) approaches in animal health (AH) makes it possible to addres...

Robot-Based Assessment of HIV-Related Motor and Cognitive Impairment for Neurorehabilitation.

There is a pressing need for strategies to slow or treat the progression of functional decline in pe...

R-JaunLab: Automatic Multi-Class Recognition of Jaundice on Photos of Subjects with Region Annotation Networks.

Jaundice occurs as a symptom of various diseases, such as hepatitis, the liver cancer, gallbladder o...

Application of machine learning methods to pathogen safety evaluation in biological manufacturing processes.

The production of recombinant therapeutic proteins from animal or human cell lines entails the risk ...

Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response.

Predictive models are becoming more and more commonplace as tools for candidate antigen discovery to...

Domain-Scan: Combinatorial Sero-Diagnosis of Infectious Diseases Using Machine Learning.

The presence of pathogen-specific antibodies in an individual's blood-sample is used as an indicatio...

Panoptic Feature Fusion Net: A Novel Instance Segmentation Paradigm for Biomedical and Biological Images.

Instance segmentation is an important task for biomedical and biological image analysis. Due to the ...

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. Owi...

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. Th...

Let's not be indifferent about robots: Neutral ratings on bipolar measures mask ambivalence in attitudes towards robots.

Ambivalence, the simultaneous experience of both positive and negative feelings about one and the sa...

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

MRI reconstruction is the key technology to accelerate MR acquisition. Recent cascade models have ga...

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 predicti...

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 ...

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 ...

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