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Universal precautions

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

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Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy's impact on ART adherence.

Adherence to antiretroviral therapy (ART) is critical for HIV treatment success, yet the impact of t...

Machine learning algorithms to predict the risk of admission to intensive care units in HIV-infected individuals: a single-centre study.

Antiretroviral therapy (ART) has transformed HIV from a rapidly progressive and fatal disease to a c...

Quantifying the Predictability of Lesion Growth and Its Contribution to Quantitative Resistance Using Field Phenomics.

Measuring individual components of pathogen reproduction is key to understanding mechanisms underlyi...

β-lactam resistance: epidemiological trends, molecular drivers, and innovative control strategies in the post-pandemic era.

SUMMARY () is a major human pathogen that can cause severe diseases such as meningitis and bacteremi...

Deep learning-based real-time detection of head and neck tumors during radiation therapy.

Clinical drivers for real-time head and neck (H&N) tumor tracking during radiation therapy (RT) are ...

Potential and challenges for application of microbiomes in agriculture.

The plant microbiome can promote plant health and productivity through a multitude of mechanisms. Ou...

Proactive recognition and early detection in communities through targeted HIV screening.

Human Immunodeficiency Virus (HIV) remains a critical public health concern, and is a significant gl...

Comparison of machine learning models to predict loss to follow-up among people with Human Immunodeficiency Virus (HIV).

OBJECTIVE: To compare different machine learning models of loss to follow-up among people with HIV (...

An automated hybrid deep learning framework for paddy leaf disease identification and classification.

In India, agriculture remains the primary source of livelihood for many people. Pathogen attacks in ...

Advancements and challenges in inverse lithography technology: a review of artificial intelligence-based approaches.

Inverse lithography technology (ILT) is a promising approach in computational lithography to address...

Bioengineering approaches to trained immunity: Physiologic targets and therapeutic strategies.

Trained immunity presents a unique target for modulating the immune response against infectious and ...

Mucociliary Clearance Inspired Nanozyme-centric Hydrogel Composites for Integrated Bacterial Detection.

The rapid movement of populations has led to the transmission and infection of pathogens, imposing a...

Machine learning reveals complex genetics of fungal resistance in sorghum grain mold.

Plant disease resistance is often a complex, polygenic trait, making its genetic dissection with tra...

Plasma proteomics for biomarker discovery in childhood tuberculosis.

Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of ...

Integrating bulk and single cell sequencing data to identify prognostic biomarkers and drug candidates in HBV associated hepatocellular carcinoma.

Hepatitis B virus (HBV) infection is a major driver of hepatocellular carcinoma (HCC), yet the mecha...

Predictiveness and drivers of highly pathogenic avian influenza outbreaks in Europe.

Avian Influenza (AI) outbreaks are on an increasing trajectory. This disease carries a substantial e...

Diagnostics of Autoimmune Hepatitis Enabled by Non-Invasive Clinical Proteomics.

BACKGROUND: Autoimmune hepatitis (AIH) may be difficult to diagnose and distinguish clinically and b...

On-Mask Magnetoelastic Sensor Network for Self-Powered Respiratory Monitoring.

Respiratory monitoring is crucial because it provides key insights into a person's health and physio...

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