Public Health & Policy

Enhanced deep learning model for anomaly object detection and tracking from surveillance videos.

Video anomaly detection plays a crucial role in video surveillance, which identifies suspicious intruders without human intervention. Moreover, the rapid growth of video surveillance applications such as intrusion detection, health monitoring systems, and fault detection provides a secure environment. Furthermore, detecting anomalous intruders from video is a challenging task because of diverse co...

An explainable artificial intelligence framework for clinical decision support in stroke discharge planning.

BACKGROUND: Stroke, a leading cause of global mortality and disability, requires accurate prediction of discharge outcomes to support early care planning. We developed an explainable artificial intelligence (AI) framework to predict four discharge categories (home, specialized care, home with help, expired) and identify key predictors. METHODS: This single-center retrospective study included 1,731...

Mapping the Global Research Landscape of Traumatic Dental Injuries in the Primary Dentition: A Bibliometric Analysis.

BACKGROUND/AIM: Traumatic dental injury (TDI) in the primary dentition represents a significant global public health problem. This study aimed to anal...

Integrating human and artificial intelligence for robust postmarketing safety surveillance systems: reflections from the FDA Sentinel Innovation Center.

OBJECTIVES: To describe considerations for integration of human and artificial intelligence for creating a postmarketing surveillance system capable o...

Machine learning-based prognosis and early death prediction in de novo stage IV breast cancer patients with bone metastasis: a SEER database and multicentre retrospective study.

Bone is the most common site of distant metastasis in breast cancer (BC), and the development of bone metastasis (BM) is associated with reduced survi...

Tree-based machine learning models recover rule-based flare labels from virtual symptom diaries in pediatric Behçet's disease: an in silico proof-of-concept study.

Behçet's disease (BD) in childhood is characterised by recurrent inflammatory flares that can result in significant morbidity, most notably with ocula...

Recent advances in machine learning and Bayesian modeling for tropical disease prediction, diagnosis, and risk analysis: a scoping review.

BACKGROUND: Enhancing the capacity to forecast tropical disease transmission, identify key risk factors, and support timely public health responses is...

Develop and validate a fair machine learning model to identify patients with high data-continuity in electronic health records data.

OBJECTIVES: Electronic health record (EHR) data discontinuity, defined as receiving care outside of a particular EHR system, may cause misclassificati...

[Transformation of Epidemiology in the Age of Artificial Intelligence].

Epidemiology has been fundamental for analyzing health problems and supporting decision-making in healthcare systems and public health. However, tradi...

Raman spectroscopic detection of salivary thiocyanate for smoking exposure stratification.

Distinguishing smokers from non-smokers and stratifying smokers based on their smoking history/exposure (years) are essential for evaluating the risk ...

An AI-Assisted Tool to Predict Continuous Glucose Monitor Adherence in Children With Type 1 Diabetes in Oman: Protocol for a Multiphase Mixed Methods Translational Study.

BACKGROUND: Type 1 diabetes mellitus (T1DM) in children requires sustained self-management to achieve glycemic targets. Continuous glucose monitoring ...

Digital infrastructures and data interoperability in radiology for prevention: from digital health to AI-enabled, quantitative imaging workflows.

Radiology is rapidly evolving from a service that produces images into a data-centric clinical platform that supports prevention, early diagnosis, and...

Machine Unlearning Based on Globally Refined Convergent Clustering for Health Survey Data-driven Prediction Model.

Machine learning models built from national health surveys enable population-scale risk stratification, yet the GDPR's "right to be forgotten" mandate...

Geospatial-based surveillance of malaria risk in dar es salaam using a hybrid 3DCNN + LSTM and CA model.

Malaria remains a significant public health burden in tropical and subtropical regions, where the efficient identification and prediction of risk area...

[Chinese guideline for the diagnosis and treatment of hospital-acquired pneumonia and ventilator-associated pneumonia in adults (2026 edition): protocol].

This document serves as the protocol for the development of the Chinese Guideline for the Diagnosis and Treatment of Hospital-Acquired Pneumonia and V...

Disparities in severe infection risk associated with systemic lupus erythematosus: evidence from a causal forest analysis.

OBJECTIVES: Severe infections are a primary cause of morbidity and premature mortality in patients with Systemic Lupus Erythematosus (SLE). Although S...

Modeling multidimensional perceived risk in HIV-related social media: a multi-label transformers framework with longitudinal analysis.

This paper presents a supervised multi-label framework for detecting multidimensional perceived risk in HIV-related Reddit discourse. A longitudinal c...

Machine learning driven modeling of synergistic perinatal risk profiles in early onset pediatric cerebral palsy.

AIM: To develop and evaluate machine learning (ML) models for early cerebral palsy (CP) prediction and identify synergistic perinatal risk factors in ...

Development and multicohort external validation of a preoperative [18F]PSMA-1007 PET-derived deep learning score and multimodal model for predicting biochemical recurrence-free survival after radical prostatectomy.

PURPOSE: To develop and validate a preoperative [18F]PSMA-1007 PET-derived deep learning score (DLS) and an integrated model combining DLS, D'Amico ri...

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model ris...