Public Health

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 emerged as a significant and potentially fatal threat. This review examines the dynamics of MPXV transmission, person-to-person spread, and infection mechanisms, highlighting key risk factors. We explore the clinical features of Mpox, focusing on sym...

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 healthcare, biotechnology, and vaccine development. These technologies offer immense potential to improve project management efficiency, decision-making, and resource utilization, especially in complex tasks such as vaccine development and healthcare i...

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...

Onset and long-term duration of immunity provided by a single vaccination with recombinant a Marek's disease virus with REV-LTR insertion.

Marek's Disease (MD), caused by Marek's disease virus (MDV), is a highly contagious lymphoproliferative disease in poultry. Despite the fact that MD h...

Evaluating generative artificial intelligence's limitations in health policy identification and interpretation.

Policy epidemiology utilizes human subject-matter experts (SMEs) to systematically surface, analyze, and categorize legally-enforceable policies. The ...

From Code to Clots: Applying Machine Learning to Clinical Aspects of Venous Thromboembolism Prevention, Diagnosis, and Management.

The high incidence of venous thromboembolism (VTE) globally and the morbidity and mortality burden associated with the disease make it a pressing issu...

Potato Late Blight Outbreak: A Study on Advanced Classification Models Based on Meteorological Data.

While past research has emphasized the importance of late blight infection detection and classification, anticipating the potato late blight infection...

VaxOptiML: leveraging machine learning for accurate prediction of MHC-I and II epitopes for optimized cancer immunotherapy.

Cancer immunotherapy hinges on accurate epitope prediction for advancing vaccine development. VaxOptiML (available at https://vaxoptiml.streamlit.app/...

Using machine learning for personalized prediction of longitudinal coronavirus disease 2019 vaccine responses in transplant recipients.

The coronavirus disease 2019 pandemic has underscored the importance of vaccines, especially for immunocompromised populations like solid organ transp...

Integrating graph and reinforcement learning for vaccination strategies in complex networks.

Pandemics like COVID-19 have a huge impact on human society and the global economy. Vaccines are effective in the fight against these pandemics but of...

Neural network procedures for the cholera disease system with public health mediations.

Severe gastrointestinal infections and watery diseases like cholera are still a major worldwide medical concern in the developing nations. A mathemati...

Evaluation of rapid detection methods for H5N1 virus using biosensors: An AI-based study.

High mortality and zoonotic potential predispose the H5N1 avian influenza virus as a critical threat. knowing that an epidemic could be occurring, qui...

Integrating Interpretability in Machine Learning and Deep Neural Networks: A Novel Approach to Feature Importance and Outlier Detection in COVID-19 Symptomatology and Vaccine Efficacy.

In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural n...