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Universal precautions

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

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A Review of the Systemic Manifestations of Hepatitis B Virus Infection, Hepatitis D Virus, Hepatocellular Carcinoma, and Emerging Therapies.

Chronic hepatitis B virus (HBV) infection affects about 262 million people worldwide, leading to ove...

Prediction sets adaptive to unknown covariate shift.

Predicting sets of outcomes-instead of unique outcomes-is a promising solution to uncertainty quanti...

Leveraging artificial intelligence in the fight against infectious diseases.

Despite advances in molecular biology, genetics, computation, and medicinal chemistry, infectious di...

Discovery of a Novel DCAF1 Ligand Using a Drug-Target Interaction Prediction Model: Generalizing Machine Learning to New Drug Targets.

DCAF1 functions as a substrate recruitment subunit for the RING-type CRL4 and the HECT family EDVP E...

Digerati - A multipath parallel hybrid deep learning framework for the identification of mycobacterial PE/PPE proteins.

The genome of Mycobacterium tuberculosis contains a relatively high percentage (10%) of genes that a...

Infection diagnosis in hydrocephalus CT images: a domain enriched attention learning approach.

. Hydrocephalus is the leading indication for pediatric neurosurgical care worldwide. Identification...

Rule ensemble method with adaptive group lasso for heterogeneous treatment effect estimation.

The increasing scientific attention given to precision medicine based on real-world data has led to ...

Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii.

Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug resista...

Intelligent convolution neural network-assisted SERS to realize highly accurate identification of six pathogenic .

Based on label-free SERS technology, the relationship between the Raman signals of pathogenic micro...

A discontinuity-preserving regularization for deep learning-based cardiac image registration.

. Sliding motion may occur between organs in anatomical regions due to respiratory motion and heart ...

Rethinking Saliency Map: A Context-Aware Perturbation Method to Explain EEG-Based Deep Learning Model.

Deep learning is widely used to decode the electroencephalogram (EEG) signal. However, there are few...

Coupling machine learning and epidemiological modelling to characterise optimal fungicide doses when fungicide resistance is partial or quantitative.

Increasing fungicide dose tends to lead to better short-term control of plant diseases. However, hig...

Stretchable and All-Directional Strain-Insensitive Electronic Glove for Robotic Skins and Human-Machine Interfacing.

Electronic gloves (e-gloves), with their multifunctional sensing capability, hold a promising applic...

Accurate Prediction of Transcriptional Activity of Single Missense Variants in HIV Tat with Deep Learning.

Tat is an essential gene for increasing the transcription of all HIV genes, and affects HIV replicat...

Machine learning at the edge for AI-enabled multiplexed pathogen detection.

Multiplexed detection of biomarkers in real-time is crucial for sensitive and accurate diagnosis at ...

NeuroSuitUp: System Architecture and Validation of a Motor Rehabilitation Wearable Robotics and Serious Game Platform.

BACKGROUND: This article presents the system architecture and validation of the NeuroSuitUp body-mac...

The predictive model for COVID-19 pandemic plastic pollution by using deep learning method.

Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of CO...

Deep learning models for hepatitis E incidence prediction leveraging meteorological factors.

BACKGROUND: Infectious diseases are a major threat to public health, causing serious medical consump...

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