Public Health & Policy

Spatiotemporal patterns of climate-sensitive vector-borne diseases in Bangladesh: leveraging machine learning and spatial regression for intervention strategies.

BACKGROUND: Bangladesh has a noticeable rise in vector-borne diseases (VBD) attributed to climate change. Accurately mapping, predicting, and identifying the risk factors of VBD is essential for prevention and control strategies. Therefore, this study aimed to investigate the spatiotemporal pattern and associated meteorological factors of VBD in Bangladesh. METHODS: This study used district-level ...

Artificial intelligence in critical synthesis of public health responses to violence: A novel application to UK violence prevention policy.

OBJECTIVES: Artificial intelligence (AI) systems are increasingly applied in public health, yet their use for analysing fragmented, multi-sectoral policy landscapes remains underdeveloped. This study aimed to describe the development and preliminary exploration of an AI-enabled tool designed to synthesise evidence from violence-related policy documents in the UK. STUDY DESIGN: An exploratory, proo...

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-pow...

Enhancing Model Generalizability in Medical Artificial Intelligence: Systematic Comparison of Categorical Encoding and Sampling Techniques for Imbalanced Data.

BACKGROUND: Despite the increasing use of machine learning (ML) in clinical research, the early stages of data preparation, especially for structured ...

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 ...

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...

A machine-learning-based tool for stroke risk prediction in blunt cerebrovascular injury: development and preliminary evaluation.

PURPOSE: Stroke risk correlates with the Biffl grading system in blunt cerebrovascular injury (BCVI). Although anti-thrombotic therapy is the mainstay...

Exposome-wide patterns predict brain health in aging.

Promoting brain health is vital for well-being and reducing healthcare burdens. Brain health as measured with the Brain Age Gap (BAG) - the difference...

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 ...

Cost-effectiveness of an artificial intelligence predictive model for guiding androgen deprivation therapy in intermediate-risk prostate cancer.

The ArteraAI Prostate Test (ArteraAI Inc.) is the first predictive biomarker for benefit of adding short-term androgen deprivation therapy (ADT) to ra...

Occlusion-activated autonomous piezoelectric implants for adaptive prevention of peri-implantitis.

More than one-third of the global population suffers from dental defects, with osseointegrated implants being the gold-standard intervention; yet, the...

Subgroup identification of disparities in buprenorphine discontinuation in opioid-use disorder: A Virtual Twins machine learning approach using nationwide United States claims data, 2006-2022.

Buprenorphine retention is crucial for effective treatment of opioid use disorder (OUD), yet disparities in treatment discontinuation persist. This st...

Governing the rise of AI in healthcare: A comparative governance document and implementation implications across five jurisdictions.

BACKGROUND: As AI increasingly reshapes healthcare delivery and innovation, global health systems face urgent imperatives to govern its development, d...

Why we need to maintain a critical view on big data and artificial intelligence predictions.

Artificial intelligence (AI) and machine learning are widely promoted as transformative tools for medical practice, yet their impact in daily rheumato...

Healthcare-associated infections in Italian long-term care facilities: a machine learning analysis of a 12-month cohort.

OBJECTIVES: To estimate the incidence of healthcare-associated infections (HAIs) in Italian long-term care facilities (LTCFs) and to evaluate whether ...

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...

Artificial intelligence in ACL injury prediction and prevention: a systematic review.

BACKGROUND: Anterior cruciate ligament (ACL) injuries are prevalent in sports, with significant physical, economic, and long-term health impacts. Arti...