Public Health

Proof of Concept of Large Language Models for Opioid Treatment Policy Surveillance: 97% Agreement With Subject Matter Experts.

OBJECTIVE: Policy surveillance typically involves detailed, time-consuming manual screening of policies for inclusion in a final dataset. This screening process involves risks of human error and inconsistent application of inclusion/exclusion criteria, especially in complicated legal landscapes like the US opioid treatment landscape. Large language models (LLMs) could assist human subject matter e...

Prognostic factors and predictive modeling of in-hospital mortality among MDRO-positive inpatients: a retrospective cohort and GBD MICROBE study.

Existing studies on prognostic prediction for multidrug-resistant organisms (MDROs) are limited by single-model designs, incomplete consideration of ward environmental observations, and insufficient linkage to national antimicrobial-resistance burden data. This single-center pilot study aimed to identify interpretable prognostic factors for in-hospital mortality among MDRO-positive inpatients, int...

Neoantigen in cancer immunotherapy: mechanism, therapeutic strategies and future perspectives.

Neoantigens are tumor-specific antigens resulting from genetic, transcriptomic, and proteomic changes, making them a promising avenue for personalized...

Identifying risk factors for marijuana use among male high school students using machine learning: Implications for public health.

OBJECTIVES: To identify risk and protective factors associated with lifetime marijuana use among male high school students through an interpretable ma...

Autonomous Vascular Access Devices: Current Solutions and Future Challenges.

INTRODUCTION: Central venous cannulation is essential for life-saving interventions including resuscitation of critically ill patients, hemodynamic mo...

Dehiscence, Infection, Seroma, Haematoma (DISH): Development and Validation of a New Classification of Surgical Site Outcomes.

BACKGROUND: Surgical site outcome (SSO) reporting lacks details of management, focuses on infection, and overlooks dehiscence, seroma and haematoma. A...

Bile extracellular vesicles for early cholangiocarcinoma detection in primary sclerosing cholangitis.

BACKGROUND & AIMS: Cholangiocarcinoma (CCA) is a major complication of primary sclerosing cholangitis (PSC), with a 20-year incidence of ∼15%. Early d...

Tactical vs. strategic: An adaptable framework for horizon-dependent dengue forecasting using data-driven approaches with serotype and climate covariates in Bangladesh.

Dengue remains a major public health problem in endemic regions, including Bangladesh. Forecasting algorithms relying on climatic variables may not ca...

Temporal shifts in public perceptions of influenza and its vaccine before, during, and after COVID-19 in a fragile nation.

BACKGROUND: Since the emergence of the COVID-19 pandemic, co-infection with COVID-19 and influenza has been associated with adverse health and economi...

Epidemiologically validated spatial modelling reveals fine-scale heat health risks.

Heat exposure drives substantial global disease and mortality burdens, making spatially explicit heat health risk assessment essential for targeted ad...

From Cardiovascular Risk Prediction to Precision Prevention: Methodological, Contextual, and Implementation Challenges.

Despite advances in risk prediction, cardiovascular prevention remains suboptimal, reflecting limitations in model architecture, incomplete integratio...

Development and validation of a machine learning-based model for identifying liver fibrosis in individuals with prior Schistosoma japonicum infection: a step toward precision management.

BACKGROUND: Liver fibrosis caused by Schistosoma japonicum may continue to progress even following successful praziquantel chemotherapy. Although live...

Use of machine learning to detect Escherichia coli in drinking water in Bangladesh.

Escherichia coli (E. coli) is a key indicator of fecal contamination in freshwater and can signal the presence of other harmful bacteria and viruses. ...

The Continuity Trap in Data Science Health Research.

Secondary use is now the ordinary condition of data science health research rather than an exception to it. Electronic health records collected for cl...

Linking bisphenol a exposure to pancreatic cancer: Evidence from population epidemiology, multi-omics screening, and cellular validation.

Bisphenol A (BPA) is a ubiquitous environmental endocrine disruptor; its association with pancreatic cancer and its potential mechanisms of action rem...

Integration of artificial intelligence in public health dentistry: applications, challenges, and future directions - a scoping review.

Artificial intelligence (AI) is transforming healthcare delivery globally, with increasing applications in public health dentistry. This scoping revie...

A review into the recent advances in the world of amoebiasis.

PURPOSE OF REVIEW: Amoebiasis is a parasitic infection caused by Entamoeba histolytica, affecting 10% of the global population. It is a well recognize...

Dissolution of Continuity of Ethical Governance in Data Science Health Research: A Diagnostic and Response Framework for Lifecycle Oversight.

Traditional research ethics governance was designed for bounded protocols, identifiable investigators, and temporally limited encounters with human pa...

Machine learning prediction of human antibiotic resistance risk using 16S rRNA profiles.

Antimicrobial resistance poses a growing global health threat, yet large-scale surveillance and risk evaluation remain constrained by the cost and acc...

Multimodal Artificial Intelligence System for Risk-Adapted Cancer Survivorship Surveillance: A Multicenter Target Trial Emulation.

BACKGROUND: The growing population of cancer survivors faces immense monitoring burdens due to rigid follow-up guidelines, such as the intensive surve...