Public Health

Application of machine learning algorithms in an epidemiologic study of mortality.

PURPOSE: Epidemiologic studies are important in assessing risk factors of mortality. Machine learning (ML) is efficient in analyzing multidimensional data to unravel dependencies between risk factors and health outcomes.

The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.

Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investigates the multidimensional role of AI in the pandemic, which arises as a global health crisis, and its role in preparedness and responses, ranging from enhanced epidemiological modelling to the acceleration of vaccine development. The confluence of A...

SVM directed machine learning classifier for human action recognition network.

Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of gu...

Leveraging AHP and transfer learning in machine learning for improved prediction of infectious disease outbreaks.

Infectious diseases significantly impact both public health and economic stability, underscoring the critical need for precise outbreak predictions to...

From Outbreaks to Artificial Intelligence: A Comprehensive Review of Monkeypox Virus Epidemiology, Diagnosis, Treatment, Vaccination, and Deep Learning Applications.

After the global impact of the COVID-19 pandemic, concerns over virus transmission have risen. A state of health emergency was declared in 2022 due t...

Bias in machine learning applications to address non-communicable diseases at a population-level: a scoping review.

BACKGROUND: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluatio...

Fluorescence excitation-emission matrix spectroscopy combined with machine learning for the classification of viruses for respiratory infections.

Significant efforts were currently being made worldwide to develop a tool capable of distinguishing between various harmful viruses through simple ana...

Correction: Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study.

[This corrects the article DOI: 10.1371/journal.pone.0257005.].

Impact of a trace mineral injection at weaning on growth, behavior, and inflammatory, antioxidant, and immune responses of beef calves.

Two experiments evaluated the effects of an injectable trace mineral (ITM) solution at weaning on trace mineral (TM) status, inflammatory and antioxid...

Predicting the infecting dengue serotype from antibody titre data using machine learning.

The development of a safe and efficacious vaccine that provides immunity against all four dengue virus serotypes is a priority, and a significant chal...

Clade Ib: a new emerging threat in the Mpox outbreak.

Monkeypox, a zoonotic virus in the , has drawn global attention for its impact on public health. In the current Mpox outbreak, a novel clade, Ib, has ...

A meta-analysis of AI and machine learning in project management: Optimizing vaccine development for emerging viral threats in biotechnology.

OBJECTIVES: Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies across various industries, including he...

Rapid Deployment of Antiviral Drugs Using Single-Virus Tracking and Machine Learning.

The outbreak of emerging acute viral diseases urgently requires the acceleration of specialized antiviral drug development, thus widely adopting pheno...

Clinical characteristics and prediction model of re-positive nucleic acid tests among Omicron infections by machine learning: a real-world study of 35,488 cases.

BACKGROUND: During the Omicron BA.2 variant outbreak in Shanghai, China, from April to May 2022, PCR nucleic acid test re-positivity (TR) occurred fre...

Sustainable integration of artificial intelligence and machine learning approaches within the African infectious disease vaccine research and development ecosystem.

Artificial Intelligence and Machine Learning (AI/ML) techniques, including reverse vaccinology and predictive models, have already been applied for de...

Policy brief: Improving national vaccination decision-making through data.

Life course immunisation looks at the broad value of vaccination across multiple generations, calling for more data power, collaboration, and multi-di...

Interpretable deep learning survival predictions in sporadic Creutzfeldt-Jakob disease.

BACKGROUND: Sporadic Creutzfeldt-Jakob disease (sCJD) is a rapidly progressive and fatal prion disease with significant public health implications. Su...

Mandatory surveillance of bacteremia conducted by automated monitoring.

Except for a few countries, comprehensive all-cause surveillance for bacteremia is not part of mandatory routine public health surveillance. We argue ...

Analysis of HIV infection among voluntary blood donors based on HIV ELISA and nucleic acid detection.

OBJECTIVE: To analyze the epidemiological characteristics of human immunodeficiency virus (HIV) infection among voluntary blood donors and provide a f...

Advanced vision transformers and open-set learning for robust mosquito classification: A novel approach to entomological studies.

Mosquito-related diseases pose a significant threat to global public health, necessitating efficient and accurate mosquito classification for effectiv...