Public Health & Policy

Adaptive Image Restoration for Video Surveillance: A Real-Time Approach

One of the major challenges in the field of computer vision especially for detection, segmentation, recognition, monitoring, and automated solutions, is the quality of images. Image degradation, often caused by factors such as rain, fog, lighting, etc., has a negative impact on automated decision-making.Furthermore, several image restoration solutions exist, including restoration models for sing...

Machine Learning Applications Related to Suicide in Military and Veterans: A Scoping Literature Review

Suicide remains one of the main preventable causes of death among active service members and veterans. Early detection and prediction are crucial in suicide prevention. Machine learning techniques have yielded promising results in this area recently. This study aims to assess and summarize current research and provides a comprehensive review regarding the application of machine learning techniqu...

Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics.

Differential equations-based epidemiological compartmental systems and deep neural networks-based artificial intelligence can effectively analyze and ...

Characterizing low femoral neck BMD in Qatar Biobank participants using machine learning models.

BACKGROUND: Identifying determinants of low bone mineral density (BMD) is crucial for understanding the underlying pathobiology and developing effecti...

Pros, Cons and Limits of AI in Public Health.

This paper explores the role of Artificial Intelligence (AI) in Public Health (PH), examining its benefits, challenges, and ethical considerations. AI...

Machine Learning-Based Clinical Decision Support System for Suicide Risk Management: The PERMANENS Project.

The PERMANENS European project addresses the global public health challenge of self-harm and suicide by developing a machine learning-based Clinical D...

Participatory Design of an AI-Based CDSS for Delirium Prevention.

Delirium is a frequent and severe complication in inpatient care, leading to increased mortality and cognitive impairment. The KIDELIR project aims to...

Development and validation of machine learning nomograms for predicting survival in stage IV pancreatic cancer: A retrospective study.

BACKGROUND: Stage IV pancreatic cancer (PC) has a poor prognosis and lacks individualized prognostic tools. Current survival prediction models are lim...

Applying AI to Support Categorization of Heterogeneous Epidemiological Datasets.

The significance of Findable, Accessible, Interoperable, and Reusable (FAIR) data is increasing, particularly in the context of enhancing data reuse i...

Practical Approach for Evaluating Machine Learning Anomaly Detection Algorithms for Epidemic Early Warning Systems.

Anomaly detection methods in time series data can play a pivotal role in epidemic surveillance Early Warning Systems (EWS). Statistical and rules-base...

WSCIF: A Weakly-Supervised Color Intelligence Framework for Tactical Anomaly Detection in Surveillance Keyframes

The deployment of traditional deep learning models in high-risk security tasks in an unlabeled, data-non-exploitable video intelligence environment ...

Predicting overactive bladder from inflammatory markers: A machine learning approach using NHANES 2005-2020.

Overactive bladder (OAB), a prevalent condition characterized by urgency and nocturia, imposes significant burdens on both quality of life and healthc...

Personalized surveillance in colorectal cancer: Integrating circulating tumor DNA and artificial intelligence into post-treatment follow-up.

Given the growing burden of colorectal cancer (CRC) as a global health challenge, it becomes imperative to focus on strategies that can mitigate its i...

"What Did You Say, ChatGPT?" The Use of AI in Black Women's HIV Self-Education: An Inductive Qualitative Data Analysis.

The emergence of widely accessible artificial intelligence (AI) chatbots such as ChatGPT presents unique opportunities and challenges in public health...

Publisher Correction: A robust and interpretable ensemble machine learning model for predicting healthcare insurance fraud.

Sex differences in bladder cancer: understanding biological and clinical implications.

Bladder cancer (BC) remains a significant global health concern, with substantial sex and racial disparities in incidence, progression, and outcomes. ...

An Interpretable AI for Smart Homes: Identifying Fall Prevention Strategies for Older Adults Using Multimodal Deep Learning.

Falls are a significant cause of mortality among older adults and are considered preventable emergencies. We developed an interpretation framework, in...

Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review.

COVID-19 was one of the most serious global public health emergencies in recent years, and its extremely fast spreading speed had a profound negative ...

Dual level dengue diagnosis using lightweight multilayer perceptron with XAI in fog computing environment and rule based inference.

Over the last fifty years, arboviral infections have made an unparalleled contribution to worldwide disability and morbidity. Globalization, populatio...

OB HUB: Remote Electronic Fetal Monitoring Surveillance.

OBJECTIVE: The purpose of this project was to implement a remote fetal surveillance unit with increased vigilance and timelier responses to electronic...