Public Health & Policy

Machine learning and deep learning tools for the automated capture of cancer surveillance data.

The National Cancer Institute and the Department of Energy strategic partnership applies advanced co...

The role of artificial intelligence-assisted endoscopy surveillance in clinical practice: controversies and future perspectives.

Surveillance of Health Care-Associated Violence Using Natural Language Processing.

BACKGROUND AND OBJECTIVES: Patient and family violent outbursts toward staff, caregivers, or through...

How Should Medicare Pay for Artificial Intelligence?

Development of an Intelligent Health Education System Based on Large Language Model for Elderly Pulmonary Aspiration Prevention.

As the aging process accelerates, the incidence of chronic diseases in the elderly is rising. As a r...

Machine learning for detection of heterogeneous effects of Medicaid coverage on depression.

In 2008, Oregon expanded its Medicaid program using a lottery, creating a rare opportunity to study ...

Diagnosing Suicidal Ideation from Resting State EEG Data Using a Machine Learning Algorithm.

Suicide poses a global health crisis with significant social and economic impact. Prevention may be ...

Predicting Diabetes in Canadian Adults Using Machine Learning.

Rising diabetes rates have led to increased healthcare costs and health complications. An estimated ...

Identifying Prediabetes in Canadian Populations Using Machine Learning.

Prediabetes is a critical health condition characterized by elevated blood glucose levels that fall ...

ECG-based Daily Activity Recognition Using 1D Convolutional Neural Networks.

This study presents an approach to human activity recognition (HAR) using electrocardiogram (ECG) si...

Unlocking Hidden Risks: Harnessing Artificial Intelligence (AI) to Detect Subclinical Conditions from an Electrocardiogram (ECG).

Recent artificial intelligence (AI) advancements in cardiovascular medicine offer potential enhancem...

Through the Looking Glass Darkly: How May AI Models Influence Future Underwriting?

Applications of Artificial Intelligence (AI) deep-learning models to screening for clinical conditio...

Implementation of a machine learning model in acute coronary syndrome and stroke risk assessment for patients with lower urinary tract symptoms.

OBJECTIVE: The global population is aging and the burden of lower urinary tract symptoms (LUTS) is e...

Automated cooling tower detection through deep learning for Legionnaires' disease outbreak investigations: a model development and validation study.

BACKGROUND: Cooling towers containing Legionella spp are a high-risk source of Legionnaires' disease...

Use of artificial intelligence for health care-associated infection surveillance: Correspondence.

Response to the letter to the editor regarding "Assisting the Infection Preventionist: Use of Artificial Intelligence for Healthcare-Associated Infection Surveillance".

Streamlining social media information retrieval for public health research with deep learning.

OBJECTIVE: Social media-based public health research is crucial for epidemic surveillance, but most ...

Predicting the transmission trends of COVID-19: an interpretable machine learning approach based on daily, death, and imported cases.

COVID-19 is caused by the SARS-CoV-2 virus, which has produced variants and increasing concerns abou...

Harnessing causal forests for epidemiologic research: key considerations.

Assessing heterogeneous treatment effects (HTEs) is an essential task in epidemiology. The recent in...

From GeoSentinel data to epidemiological insights: a multidisciplinary effort towards artificial intelligence-supported detection of infectious disease outbreaks.

Application of improved glomerular filtration rate estimation by a neural network model in patients with neurogenic lower urinary tract dysfunction.

BACKGROUND: Previous studies have indicated that creatinine (Cr)-based glomerular filtration rate (G...