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Universal precautions

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

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Characterization of the prevalence of Salmonella in different retail chicken supply modes using genome-wide and machine-learning analyses.

Salmonella is a foodborne pathogen that causes salmonellosis, of which retail chicken meat is a majo...

Identification of hepatic steatosis among persons with and without HIV using natural language processing.

BACKGROUND: Steatotic liver disease (SLD) is a growing phenomenon, and our understanding of its dete...

Classification of white blood cells (leucocytes) from blood smear imagery using machine and deep learning models: A global scoping review.

Machine learning (ML) and deep learning (DL) models are being increasingly employed for medical imag...

A deep-learning-based model for assessment of autoimmune hepatitis from histology: AI(H).

Histological assessment of autoimmune hepatitis (AIH) is challenging. As one of the possible results...

Development of a real-time cattle lameness detection system using a single side-view camera.

Recent advancements in machine learning and deep learning have revolutionized various computer visio...

Combining machine learning with high-content imaging to infer ciprofloxacin susceptibility in isolates of Salmonella Typhimurium.

Antimicrobial resistance (AMR) is a growing public health crisis that requires innovative solutions....

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy.

Tuberculosis (TB) is the world's deadliest infectious disease, with over 1.5 million deaths and 10 m...

Machine learning in infectious diseases: potential applications and limitations.

Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligenc...

Assessing the risk of E. coli contamination from manure application in Chinese farmland by integrating machine learning and Phydrus.

This study aims to present a comprehensive study on the risks associated with the residual presence ...

Protein function annotation and virulence factor identification of Klebsiella pneumoniae genome by multiple machine learning models.

Klebsiella pneumoniae is a type of Gram-negative bacterium which can cause a range of infections in ...

Use of machine learning approaches to predict transition of retention in care among people living with HIV in South Carolina: a real-world data study.

Maintaining retention in care (RIC) for people living with HIV (PLWH) helps achieve viral suppressio...

Comparative analysis of different Karnal bunt disease prediction models developed by machine learning techniques for Punjab conditions.

Timely prediction of pathogen is important key factor to reduce the quality and yield losses. Wheat ...

A machine learning-based model analysis for serum markers of liver fibrosis in chronic hepatitis B patients.

Early assessment and accurate staging of liver fibrosis may be of great help for clinical diagnosis ...

Improving HIV preexposure prophylaxis uptake with artificial intelligence and automation: a systematic review.

OBJECTIVES: To identify studies promoting the use of artificial intelligence (AI) or automation with...

Improved brain metastases segmentation using generative adversarial network and conditional random field optimization mask R-CNN.

BACKGROUND: In radiotherapy, the delineation of the gross tumor volume (GTV) in brain metastases usi...

Machine learning for predicting cognitive deficits using auditory and demographic factors.

IMPORTANCE: Predicting neurocognitive deficits using complex auditory assessments could change how c...

Predicting the age of field mosquitoes using mass spectrometry and deep learning.

Mosquito-borne diseases like malaria are rising globally, and improved mosquito vector surveillance ...

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