Infectious Disease

Public Health

Latest AI and machine learning research in public health for healthcare professionals.

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Artificial intelligence in vaccine research and development: an umbrella review.

BACKGROUND: The rapid development of COVID-19 vaccines highlighted the transformative potential of artificial intelligence (AI) in modern vaccinology, accelerating timelines from years to months. Nevertheless, the specific roles and effectiveness of AI in accelerating and enhancing vaccine research, development, distribution, and acceptance remain dispersed across various reviews, underscoring the...

Jan 1 2025 40406131

IoT and ML-driven framework for managing infectious disease risks in communal spaces: a post-COVID perspective.

COVID-19 has not only changed the way people live but has also altered the way all organizations operate. The most effective precautionary measure against the spread of the virus that caused the COVID-19 pandemic SARS-CoV-2, is to use face coverings in public settings. In this study, we present a potential application of the Internet of Things (IoT) and machine learning to prevent the spread of CO...

Jan 1 2025 40438060
Cholera Outbreak in Nigeria: History, Review of Socioeconomic and Meteorological Drivers, Diagnostic Challenges, and Artificial Intelligence Integration.

Cholera continues to pose a significant public health challenge in Nigeria, driven by socioeconomic disparities, poor sanitation, and environmental fa...

Jan 1 2025 40469257
Anomaly recognition in surveillance based on feature optimizer using deep learning.

Surveillance systems are integral to ensuring public safety by detecting unusual incidents, yet existing methods often struggle with accuracy and robu...

Jan 1 2025 40388481
Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac using machine learning.

Meningococcal meningitis poses a significant public health burden in the meningitis belt region of sub-Saharan Africa. The introduction of the meningo...

Jan 1 2025 40367245
EACVP: An ESM-2 LM Framework Combined CNN and CBAM Attention to Predict Anti-coronavirus Peptides.

BACKGROUND: The novel coronavirus pneumonia (COVID-19) outbreak in late 2019 killed millions worldwide. Coronaviruses cause diseases such as severe ac...

Jan 1 2025 38494930
Leveraging artificial intelligence to promote COVID-19 appropriate behaviour in a healthcare institution from north India: A feasibility study.

Background & Objectives Non-pharmacological interventions (NPI) were crucial in curbing the initial COVID-19 pandemic waves, but compliance was diffic...

Jan 1 2025 40036109
What drives the effectiveness of social distancing in combating COVID-19 across U.S. states?

We propose a new theory of information-based voluntary social distancing in which people's responses to disease prevalence depend on the credibility o...

Jan 1 2025 40354357
Ensemble learning guided survival prediction and chemotherapy benefit analysis in high-grade chondrosarcoma: A study based on the surveillance, epidemiology, and end results (SEER) database.

The chemotherapy benefit for high-grade chondrosarcoma remains controversial. Ensemble learning has better overall performance than single computatio...

Jan 1 2025 40346788
A conceptual and computational framework for modeling the complex, adaptive dynamics of epidemics: The case of the SARS-CoV-2 pandemic in Mexico.

In the quest to ensure adequate preparedness for health emergencies caused by infectious disease pandemics, there is a need for tools that can address...

Jan 1 2025 40341262
Analyzing Country-Level Vaccination Rates and Determinants of Practical Capacity to Administer COVID-19 Vaccines

The COVID-19 vaccine development, manufacturing, transportation, and administration proved an extreme logistics operation of global magnitude. Globa...

Iterative structural coarse-graining for contagion dynamics in complex networks

Contagion dynamics in complex networks drive critical phenomena such as epidemic spread and information diffusion,but their analysis remains computa...

Spectral Enhancement and Pseudo-Anchor Guidance for Infrared-Visible Person Re-Identification

The development of deep learning has facilitated the application of person re-identification (ReID) technology in intelligent security. Visible-infr...

Post-pandemic social contacts in Italy: implications for social distancing measures on in-person school and work attendance

The collection of updated data on social contact patterns following the COVID-19 pandemic disruptions is crucial for future epidemiological assessme...

Surveillance Capitalism Revealed: Tracing The Hidden World Of Web Data Collection

This study investigates the mechanisms of Surveillance Capitalism, focusing on personal data transfer during web navigation and searching. Analyzing...

Quantifying Public Response to COVID-19 Events: Introducing the Community Sentiment and Engagement Index

This study introduces the Community Sentiment and Engagement Index (CSEI), developed to capture nuanced public sentiment and engagement variations o...

Neuromorphic Spiking Neural Network Based Classification of COVID-19 Spike Sequences

The availability of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus data post-COVID has reached exponentially to an enormous magn...

Multi-concept Model Immunization through Differentiable Model Merging

Model immunization is an emerging direction that aims to mitigate the potential risk of misuse associated with open-sourced models and advancing ada...

Assessing the effectiveness of test-trace-isolate interventions using a multi-layered temporal network

In the early stage of an infectious disease outbreak, public health strategies tend to gravitate towards non-pharmaceutical interventions (NPIs) giv...

Spatio-Temporal SIR Model of Pandemic Spread During Warfare with Optimal Dual-use Healthcare System Administration using Deep Reinforcement Learning

Large-scale crises, including wars and pandemics, have repeatedly shaped human history, and their simultaneous occurrence presents profound challeng...

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