Public Health

Cholera resurges in Zambia: Challenges and future directions.

Cholera remains a major global health challenge, disproportionately affecting low-income countries with inadequate water, sanitation, and hygiene (WASH) infrastructure. Zambia, historically prone to outbreaks, experienced a severe resurgence in 2023-2024, with over 10,887 cases and 432 deaths. The contributing factors include poor WASH access, systemic health care weaknesses, stigma, and logistica...

Development and Validation of Models for Preoperative Prediction of Risk and Postoperative Detection of Noninfectious Complications Using Interpretable Machine Learning and Electronic Health Record Data.

OBJECTIVE: To apply interpretable machine learning methodology to electronic health record data to develop models for preoperative risk estimation and postoperative detection of noninfectious postoperative complications. SUMMARY BACKGROUND DATA: We previously developed preoperative risk and postoperative detection models for the surveillance of postoperative infections. The purpose of the present ...

Explainable AI for Symptom-Based Detection of Monkeypox: a machine learning approach.

BACKGROUND: Monkeypox, a viral zoonotic disease, is an emerging global health concern, with rising incidence and outbreaks extending beyond its endemi...

[Artificial intelligence in Public Health: opportunities, ethical challenges and future perspectives].

Artificial Intelligence (AI) is transforming Public Health by providing innovative tools to address complex global challenges. Its ability to analyze ...

Leveraging artificial intelligence to assess the impact of COVID-19 on the teacher-student relationship in higher education.

The teacher-student relationship has far-reaching implications for educational outcomes at the tertiary level. Teachers contribute to students' succes...

Developing cholera outbreak forecasting through qualitative dynamics: Insights into Malawi case study.

Cholera, an acute diarrheal disease, is a serious concern in developing and underdeveloped areas. A qualitative understanding of cholera epidemics aim...

Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.

Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress...

Spatio-temporal epidemic forecasting using mobility data with LSTM networks and attention mechanism.

The outbreak of infectious diseases can have profound impacts on socio-economic balances globally. Accurate short-term forecasting of infectious disea...

Formative Research for the Development and Implementation of a Smartphone Application to Report Breaches to the International Code of Marketing of Breast-Milk Substitutes in Mexico.

Almost 40 years after the adoption of the International Code of Marketing of Breast-Milk Substitutes ('the Code') in Mexico, noncompliance persists. I...

ListPred: A predictive ML tool for virulence potential and disinfectant tolerance in Listeria monocytogenes.

Despite current surveillance and sanitation strategies, foodborne pathogens continue to threaten the food industry and public health. Whole genome seq...

Enhancing Relation Extraction for COVID-19 Vaccine Shot-Adverse Event Associations with Large Language Models.

OBJECTIVE: The rapid evolution of the COVID-19 virus has led to the development of different vaccine shots, each designed to combat specific variants ...

Modifiable risk factors of vaccine hesitancy: insights from a mixed methods multiple population study combining machine learning and thematic analysis during the COVID-19 pandemic.

BACKGROUND: Vaccine hesitancy, the delay in acceptance or reluctance to vaccinate, ranks among the top threats to global health. Identifying modifiabl...

Unraveling the power of NAP-CNB's machine learning-enhanced tumor neoantigen prediction.

In this study, we present a proof-of-concept classical vaccination experiment that validates the in silico identification of tumor neoantigens (TNAs) ...

Epidemiology and risk factors of Clonorchis sinensis infection in the mountainous areas of Longsheng County, Guangxi: insights from automated machine learning.

Clonorchis sinensis (C. sinensis) is mainly prevalent in Northeast and South China, with Guangxi being the most severely affected region. This study a...

Efficacy and Safety of a Medical Robot for Non-Face-to-Face Nasopharyngeal Swab Specimen Collection: Nonclinical and Clinical Trial Findings for COVID-19 Testing.

ObjectivesTo meet the high demand for polymerase chain reaction (PCR) tests to diagnose COVID-19 and rapidly control the outbreak, an efficient and sa...

CEL: A Continual Learning Model for Disease Outbreak Prediction by Leveraging Domain Adaptation via Elastic Weight Consolidation.

Continual learning is the ability of a model to learn over time without forgetting previous knowledge. Therefore, adapting new data in dynamic fields ...

Artificial intelligence in public health: promises, challenges, and an agenda for policy makers and public health institutions.

Artificial intelligence (AI) can rapidly analyse large and complex datasets, extract tailored recommendations, support decision making, and improve th...

Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination.

The rapid deployment of COVID-19 vaccines has necessitated the ongoing surveillance of adverse events, with abnormal uterine bleeding (AUB) emerging a...

Machine learning-based prediction model for patients with recurrent Staphylococcus aureus bacteremia.

BACKGROUND: Staphylococcus aureus bacteremia (SAB) remains a significant contributor to both community-acquired and healthcare-associated bloodstream ...

Predicting sleep quality among college students during COVID-19 lockdown using a LASSO-based neural network model.

BACKGROUND: In March 2022, a new outbreak of COVID-19 emerged in Quanzhou, leading to the implementation of strict lockdown management measures in col...