Infectious Disease

Latest AI and machine learning research in infectious disease for healthcare professionals.

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Distilling knowledge from graph neural networks trained on cell graphs to non-neural student models.

The development and refinement of artificial intelligence (AI) and machine learning algorithms have ...

Pulmonary diseases accurate recognition using adaptive multiscale feature fusion in chest radiography.

Pulmonary disease can severely impair respiratory function and be life-threatening. Accurately recog...

Machine Learning-Enhanced Nanozyme Sensor Array for Accurate Multiple Quinolone Antibiotics Recognition.

The overuse of quinolone antibiotics (QNs) seriously endangers human health and the ecological envir...

Pharmacovigilance in Cell and Gene Therapy: Evolving Challenges in Risk Management and Long-Term Follow-Up.

Cell and gene therapies, including CAR T-cells, CRISPR-based genome editing, and next-generation vir...

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...

Beyond genomics: a multiomics future for parasitology.

Parasitology has long relied on genomics and transcriptomics to explore gene function, diversity, an...

How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach.

OBJECTIVES: To identify relevant objective variables for retrospective identification of 'suspected ...

Enhancing India's Health Security Efforts Against  : Gaps and Opportunities.

India bears a quarter of the world's tuberculosis (TB) burden. In 2018, the country set an ambitious...

Predicting COVID-19 severity in pediatric patients using machine learning: a comparative analysis of algorithms and ensemble methods.

COVID-19 has posed a significant global health challenge, affecting individuals across all age group...

Deep learning approach for automated hMPV classification.

Human metapneumovirus (hMPV) is a significant cause of respiratory illness, particularly in children...

A neural network model enables worm tracking in challenging conditions and increases signal-to-noise ratio in phenotypic screens.

High-resolution posture tracking of C. elegans has applications in genetics, neuroscience, and drug ...

A Cohort Study of Pediatric Severe Community-Acquired Pneumonia Involving AI-Based CT Image Parameters and Electronic Health Record Data.

INTRODUCTION: Community-acquired pneumonia (CAP) is a significant concern for children worldwide and...

LGD_Net: Capsule network with extreme learning machine for classification of lung diseases using CT scans.

Lung diseases (LGDs) are related to an extensive range of lung disorders, including pneumonia (PNEUM...

Pharmacovigilance: Overview of Italian and European regulations, tools, and perspectives.

BackgroundThis study provides a concise overview of the Italian and European pharmacovigilance (PV) ...

Ensemble-based sesame disease detection and classification using deep convolutional neural networks (CNN).

This study presents an ensemble-based approach for detecting and classifying sesame diseases using d...

Probability-Based Early Warning for Seasonal Influenza in China: Model Development Study.

BACKGROUND: Seasonal influenza is a major global public health concern, leading to escalated morbidi...

Quantum Federated Learning in Healthcare: The Shift from Development to Deployment and from Models to Data.

Healthcare organizations have a high volume of sensitive data and traditional technologies have limi...

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