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Universal precautions

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

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Physalis Calyx seu Fructus relieves chicken intestinal damage to heat via improving the antioxidant ability.

Heat-stress-induced oxidative and inflammatory responses were important factors contributing to chic...

A graph neural network-based model with out-of-distribution robustness for enhancing antiretroviral therapy outcome prediction for HIV-1.

Predicting the outcome of antiretroviral therapies (ART) for HIV-1 is a pressing clinical challenge,...

deep-AMPpred: A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities.

Antimicrobial peptides (AMPs) are small peptides that play an important role in disease defense. As ...

A high-throughput ResNet CNN approach for automated grapevine leaf hair quantification.

The hairiness of the leaves is an essential morphological feature within the genus Vitis that can se...

Novel silver nanoparticle-based biomaterials for combating biofilms.

BACKGROUND: is a significant nosocomial pathogen that has developed resistance to multiple antibiot...

Enhanced Sampling Simulations of RNA-Peptide Binding Using Deep Learning Collective Variables.

Enhanced sampling (ES) simulations of biomolecular recognition, such as binding small molecules to p...

Isolation, identification and characteristics of from diseased rainbow trout ().

is an opportunistic pathogen that can infect humans, animals and aquatic species, which is widely d...

DFCL: Dual-pathway fusion contrastive learning for blind single-image visible watermark removal.

Digital image watermarking is a prevalent method for image copyright protection. As watermark embedd...

STI/HIV risk prediction model development-A novel use of public data to forecast STIs/HIV risk for men who have sex with men.

A novel automatic framework is proposed for global sexually transmissible infections (STIs) and HIV ...

Use of Machine Learning to Assess the Management of Uncomplicated Urinary Tract Infection.

IMPORTANCE: Uncomplicated urinary tract infection (UTI) is a common indication for outpatient antimi...

Noninvasive diagnosis of significant liver fibrosis in patients with chronic hepatitis B using nomogram and machine learning models.

This study aims to construct and validate noninvasive diagnosis models for evaluating significant li...

Fibrosis and inflammatory activity diagnosis of chronic hepatitis C based on extreme learning machine.

The traditional diagnosis of chronic hepatitis C usually relies on liver biopsy. Diagnosing chronic ...

Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to purine metabolism-associated genes.

Sepsis, characterized as a systemic inflammatory response triggered by pathogen invasion, represents...

Deaf futurity: designing and innovating hearing aids.

One of the tenets of a posthuman vision is the eradication of disability through technology. Within ...

Boosting Your Context by Dual Similarity Checkup for In-Context Learning Medical Image Segmentation.

The recent advent of in-context learning (ICL) capabilities in large pre-trained models has yielded ...

MEFA-Net: A mask enhanced feature aggregation network for polyp segmentation.

Accurate polyp segmentation is crucial for early diagnosis and treatment of colorectal cancer. This ...

A drop dispenser for simplifying on-farm detection of foodborne pathogens.

Nucleic-acid biosensors have emerged as useful tools for on-farm detection of foodborne pathogens on...

A deep learning-based ADRPPA algorithm for the prediction of diabetic retinopathy progression.

As an alternative to assessments performed by human experts, artificial intelligence (AI) is current...

RePaIR: Repaired pruning at initialization resilience.

Over the past decade, the size of neural network models has gradually increased in both breadth and ...

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