Public Health

Toward AI-Powered Cancer Etiology Research.

Advances in multimodal longitudinal data and artificial intelligence (AI) create new opportunities for cancer etiology research. We envision an AI-powered discovery workflow integrating an interoperable epidemiologic data ecosystem and causal inference frameworks to accelerate the identification of both cancer causes and the converging biological states for prevention.

Development and Validation of a Web Calculator for Predicting the Risk of Lower Limb Varicose Veins.

The aims of the present study were to develop and validate a predictive model for lower limb Varicose Veins, and to visualize the results using a web calculator for assessing the probability of patients developing Lower Limb Varicose Veins. A convenience sampling method was employed to select 421 patients from December 2023 to April 2024 at the health check-up center and vascular surgery outpatien...

Personalized neoantigen cancer vaccines: Why clinical benefit remains inconsistent.

Personalized cancer vaccines have re-emerged as a promising strategy in precision immunotherapy, driven by advances in tumor sequencing, neoantigen id...

Translational Research to Maximize the Impact of e-Oral Health.

The rapid development of digital technologies is reshaping oral health research and care delivery. However, the translation of these innovations into ...

Artificial intelligence in microbiology: implications for metagenomics, diagnostics, and AMR surveillance.

Artificial intelligence (AI) is now a key player in modern microbiology, as it enables high-resolution analyses of genomic, metagenomic, and clinical ...

Artificial intelligence at the frontlines: Emerging infectious and parasitic diseases in the digital era.

Emerging infectious diseases are one of the most significant threats to global health, driven by many factors such as zoonotic spillovers, climate cha...

AI in Oral Health Surveillance: Critical Review.

Artificial intelligence (AI) holds transformative potential for advancing oral health surveillance by streamlining data collection, integration, and d...

The emergence of superficial dermatophytosis due to Trichophyton indotineae and Trichophyton mentagrophytes genotypes VII and II* in New York: a need for comprehensive testing approaches.

We report a rapid increase in dermatophyte infections in New York City and surrounding counties from 2022 to 2024. Reported cases include 135 of Trich...

Dynamic Surveillance of the Cardiovascular Risk and Identification of Treatment Responders in Type 2 Diabetes Using A Machine Learning-Based Model.

AIMS: To establish a model to predict cardiovascular risk and identify treatment response for patients with type 2 diabetes. METHODS: Data from 11677 ...

MosQNet-SA: Explainable convolutional-attention network for mosquito classification with application as a RESTful API for dengue and malaria risk mapping.

Mosquito-borne diseases represent a significant global health challenge. Over 700,000 people succumb to mosquito-borne diseases annually, highlighting...

Deep learning-enabled scaffolding of spatial arrays of PfCSP epitopes.

Malaria is a leading cause of disease in developing countries. The licensed malaria vaccine RTS,S/AS01 confers partial protection in part due to the e...

Neural Network Machine Learning for Determining Surgical Appropriateness in Head and Neck Subspecialty Referrals.

OBJECTIVE: Timely, accurate referrals to head and neck cancer surgery are essential for survival but are often delayed or misrouted, contributing to l...

Comparison of Artificial Intelligence Tools With Human Coding for Sentiment, Topic, and Thematic Analysis Tasks of Public Health Datasets During the COVID-19 Pandemic in Australia: Case Study.

BACKGROUND: Public opinion, which may be influenced by personal experiences, news, and social media, can impact compliance with public health measures...

Predicting public Intensive care unit mortality and hospitalization using Data: An evaluation of Brazil's Largest COVID-19 epidemiological dataset.

OBJECTIVES: To assess the SRAG dataset's potential for modeling COVID-19 mortality and LOS-ICU, identify key data gaps, and support the development of...

Explainable machine learning with SHAP decodes the heterogeneous burden of nasopharyngeal carcinoma in high-risk aging Asia.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a global public health concern, with a particularly high burden concentrated in East Asia, Southeast Asi...

Artificial Intelligence-Enabled Prediction of Reversible Versus Irreversible Chemotherapy-Induced Myocardial Injury: Toward Precision Cardio-Oncology.

Cancer therapy-related cardiac dysfunction remains a major cause of morbidity among cancer survivors and may interrupt life-saving oncologic therapy o...

It Is the Journey, Not the Destination: Moving From End Points to Trajectories When Assessing Chatbot Mental Health Safety.

Large language models are rapidly becoming embedded in everyday life through artificial intelligence (AI) chatbots that people use for practical assis...

A responsible AI framework for infection surveillance in low-resource settings: ethics, opportunities and threats for LMICs (EOT-LMICs).

The integration of artificial intelligence (AI) into infection surveillance represents a significant shift in public health; however, most AI framewor...

Automated detection of tooth loss using tooth numbering segmentation in 3D intraoral scans from a population-based sample with artificial intelligence.

OBJECTIVES: This study aimed to validate an automated method for detecting tooth loss in intraoral scans (IOS) compared to clinical evaluations in a p...

Assessing plague risk across seven decades of environmental change in Inner Mongolia, China: An interpretable machine learning.

Plague, caused by Yersinia pestis, persists as a public health threat, particularly in natural foci such as China's Inner Mongolia Autonomous Region. ...