Public Health

Using machine learning to forecast peak health care service demand in real-time during the 2022-23 winter season: A pilot in England, UK.

During winter months, there is increased pressure on health care systems in temperature climates due to seasonal increases in respiratory illnesses. Providing real-time short-term forecasts of the demand for health care services helps managers plan their services. During the Winter of 2022-23 we piloted a new forecasting pipeline, using existing surveillance indicators which are sensitive to incre...

Identification of potential biomarkers for 2022 Mpox virus infection: a transcriptomic network analysis and machine learning approach.

Monkeypox virus (MPXV), a zoonotic pathogen, re-emerged in 2022 with the Clade IIb variant, raising global health concerns due to its unprecedented spread in non-endemic regions. Recent studies have shown that Clade IIb (2022 MPXV) is marked by unique genomic mutations and epidemiological behaviors, suggesting variations in host-virus interactions. This study aimed to identify the differentially e...

Real-time detection and monitoring of public littering behavior using deep learning for a sustainable environment.

With the global population surpassing 8 billion, waste production has skyrocketed, leading to increased pollution that adversely affects both terrestr...

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to na...

Machine Learning Potential for Identifying and Forecasting Complex Environmental Drivers of Infections in the United States.

BACKGROUND: Environmental change in coastal areas can drive marine bacteria and resulting infections, such as those caused by , with both foodborne an...

AI Can Be a Powerful Social Innovation for Public Health if Community Engagement Is at the Core.

There is a critical need for community engagement in the process of adopting artificial intelligence (AI) technologies in public health. Public health...

Humoral and cell-mediated immune responses to COVID-19 vaccines up to 6 months post three-dose primary series in adults with inborn errors of immunity and their breakthrough infections.

PURPOSE: Many individuals with inborn errors of immunity (IEIs) have poor humoral immune (HI) vaccine responses. Only a few studies have examined spec...

Computational biology and artificial intelligence in mRNA vaccine design for cancer immunotherapy.

Messenger RNA (mRNA) vaccines offer an adaptable and scalable platform for cancer immunotherapy, requiring optimal design to elicit a robust and targe...

Bacterial Wastewater-Based Epidemiology Using Surface-Enhanced Raman Spectroscopy and Machine Learning.

Although wastewater-based epidemiology has been used extensively for the surveillance of viral diseases, it has not been used to a similar extent for ...

Artificial intelligence and machine learning in veterinary medicine: a regulatory perspective on current initiatives and future prospects.

The US FDA's Center for Veterinary Medicine (CVM) is advancing its leadership in veterinary science by integrating AI and machine learning (ML) into i...

Role of Artificial Intelligence in Identifying Vital Biomarkers with Greater Precision in Emergency Departments During Emerging Pandemics.

The COVID-19 pandemic has accelerated advances in molecular biology and virology, enabling the identification of key biomarkers to differentiate betwe...

A comparison of the persuasiveness of human and ChatGPT generated pro-vaccine messages for HPV.

INTRODUCTION: Public health messaging is crucial for promoting beneficial health outcomes, and the latest advancements in artificial intelligence offe...

Leveraging dynamics informed neural networks for predictive modeling of COVID-19 spread: a hybrid SEIRV-DNNs approach.

A dynamics informed neural networks (DINNs) incorporating the susceptible-exposed-infectious-recovered-vaccinated (SEIRV) model was developed to enhan...

Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making.

Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater-based Surveillance (WBS), has proven a valuab...

Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges.

Integrating prior epidemiological knowledge embedded within mechanistic models with the data-mining capabilities of artificial intelligence (AI) offer...

A comprehensive retrospect on the current perspectives and future prospects of pneumoconiosis.

Pneumoconiosis is a widespread occupational pulmonary disease caused by inhalation and retention of dust particles in the lungs, is characterized by c...

The influence of factors related to public health campaigns on vaccination behavior among population of Wuxi region, China.

BACKGROUND: Public health campaigns are essential for promoting vaccination behavior, but factors such as socioeconomic status, geographical location,...

Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study.

Screening tests for disease have their performance measured through sensitivity and specificity, which inform how well the test can discriminate betwe...

Isolation, identification and characteristics of from diseased rainbow trout ().

is an opportunistic pathogen that can infect humans, animals and aquatic species, which is widely distributed in different aquatic environments and p...

High performance COVID-19 screening using machine learning.

Since the World Health Organization declared the Coronavirus Disease 2019 (COVID-19) pandemic as an international concern of public health emergency i...