Public Health

Explainable AI for public health surveillance: investigating the persistent crisis of intentional injury mortality (suicide and homicide) in the Americas.

Intentional injury mortality (IIM), comprising homicide and suicide, remains a critical public health crisis in the Americas, which not only has the highest regional homicide rates globally but is also the only region where suicide rates continue to rise. This study employs explainable artificial intelligence (XAI) to examine the structural and temporal drivers of IIM across 25 countries, based on...

Development, validation, and implementation of the antibody-secreting cell maturity index: Universal prediction of human plasma cell maturity.

Defining the maturity of long-lived antibody-secreting cells (ASCs) is important for vaccine optimization and research into autoimmune diseases, but current assessment of plasma cell maturity is limited. We developed a universal, robust method to define plasma cell maturity using a meta-analysis of public, human cytometry data, with harmonized expression of ASC maturity markers across samples. Vac...

Domain adaptive uplift modeling across heterogeneous mental health cohorts.

Predicting who will deteriorate under stress is important for targeting mental-health support; yet, treatment-effect models are rarely tested across p...

Environmental Antibiotic Contamination and AMR: Integrating Pathways, Impacts, and AI-Driven Mitigation.

The widespread contamination of the environment with antibiotic residues is a significant factor contributing to the global crisis of antimicrobial re...

Lung Cancer Screening and Prevention: Beyond Conventional Strategies in a Rapidly Changing Global Milieu.

Lung cancer remains the leading cause of cancer-related mortality worldwide despite advances in early detection and treatment. Furthermore, its epidem...

Statistical Models Addressing Acute Respiratory Diseases: A Scoping Review.

This review highlights the application of statistical models in addressing respiratory diseases worldwide. A scoping review was conducted following Jo...

Integrating AI Scribe Technology into Public Health Workflows: Simulation and Field Evaluation in Disease Case Management.

The growing integration of generative artificial intelligence (GenAI) into clinical documentation offers new opportunities to enhance public health su...

Predicting COVID-19 Vaccination Decision-Making Profiles Among Dutch Adults: From Survey to National Administrative Data.

Individual's vaccination behaviors are influenced by factors such as values and beliefs. Applying latent class analysis (LCA) to such factors from the...

From Clinical Data Warehouses to Epidemiological Indicators: A Methodology for Real-Time Surveillance.

Clinical data warehouses (CDWs) provide a robust foundation for generating real-world epidemiological indicators from electronic health records. By ex...

ASO Special Article: Proceedings of the Inaugural Joint US-India Cancer Dialogue: Accelerating Collaboration to Advance Cancer Prevention, Early Detection, Treatment, and Care.

BACKGROUND: Cancer is a leading cause of death in both the USA and India. During Prime Minister Narendra Modi's State Visit to Washington, DC in June ...

Japanese-Language AI Agent System for Human Papillomavirus Vaccine Infoveillance and Public Communication: Development and Feasibility Evaluation.

BACKGROUND: Human papillomavirus (HPV) vaccine hesitancy remains a significant public health challenge in Japan, where proactive vaccination recommend...

Enhancing respiratory virus surveillance among hospitalised children: a machine learning-based predictive model.

BACKGROUND: Viral respiratory tract infections (vRTIs) are a leading cause of paediatric hospitalisation and healthcare utilisation. Existing syndromi...

Data fusion in air pollution exposure assessment: Methods, applications, and future directions.

Over the past two decades, major advances in observational techniques and modeling capabilities have enabled the development of air pollution data fus...

Antibiotic therapy in febrile neutropenia in haematological patients: current considerations and future challenges.

The management of febrile neutropenia (FN) in oncohematological patients is undergoing a paradigm shift driven by a deeper understanding of patients' ...

Unveiling Viral Escape Mechanisms With Machine Learning: A Transformative Approach to Mutation Analysis for SARS-CoV-2 and Beyond.

Persistent viruses like Influenza, HIV, and Coronavirus exemplify the challenge of viral escape, significantly hindering the development of long-lasti...

Disease and Health Surveillance in Companion Animals Using Artificial Intelligence and Machine Learning.

Companion animal disease surveillance now benefits from collated databases of electronic health records and artificial intelligence. This review exami...

The One Health resistome: Integrating environmental, microbial, and human antimicrobial resistance surveillance and risk analysis in the digital age.

Antimicrobial resistance (AMR) and antibiotic resistance (ABR) represent one of the most pressing global health threats, driven by the complex interpl...

A Dynamic Machine Learning Approach to Complement Nurse-Led Clinics in Identifying High-Risk Patients with Intermittent Claudication.

OBJECTIVE: To develop and validate dynamic machine-learning models to predict 6-month adverse outcomes in intermittent claudication (IC), enabling ris...

Evaluation and enhancement of the prognostic ability of the eighth edition of TNM staging in cutaneous malignant melanoma: a population-based study, using machine learning, of 111 871 patients.

BACKGROUND: Melanoma is the fifth most common cancer in the USA and the UK, with global incidence on the rise. The TNM staging system guides treatment...

Prospects and Challenges of Personalized Immunotherapy in Breast Cancer Treatment and Long-term Cancer Management.

Breast cancer is highly heterogeneous,and different molecular subtypes exhibit significant variations in their response to immunotherapy.While signifi...