Public Health & Policy

Latest AI and machine learning research in public health & policy for healthcare professionals.

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Utilizing natural language processing for precision prevention of mental health disorders among youth: A systematic review.

BACKGROUND: The global mental health crisis has created barriers to youth mental healthcare, leaving...

Predicting sleep quality among college students during COVID-19 lockdown using a LASSO-based neural network model.

BACKGROUND: In March 2022, a new outbreak of COVID-19 emerged in Quanzhou, leading to the implementa...

Biomarkers, omics and artificial intelligence for early detection of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is frequently diagnosed in its late stages when treatment op...

The Mechanism of Bisphenol S-Induced Atherosclerosis Elucidated Based on Network Toxicology, Molecular Docking, and Machine Learning.

The increasing prevalence of environmental pollutants has raised public concern about their potentia...

The Role of Artificial Intelligence in Obesity Risk Prediction and Management: Approaches, Insights, and Recommendations.

Greater than 650 million individuals worldwide are categorized as obese, which is associated with si...

Artificial intelligence for modelling infectious disease epidemics.

Infectious disease threats to individual and public health are numerous, varied and frequently unexp...

Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.

This study examined mental health disparities among African Americans using AI and machine learning ...

Redefining prostate cancer care: innovations and future directions in active surveillance.

PURPOSE OF REVIEW: This review provides a critical analysis of recent advancements in active surveil...

Projections of single-level indirect lumbar interbody fusion volume and associated costs for Medicare patients to 2050.

BACKGROUND: Anterior, Oblique, and Lateral Lumbar Interbody Fusions (ALIF/OLIF/LLIF) are powerful mo...

Machine-learning approaches to predict individualized treatment effect using a randomized controlled trial.

Recent advancements in machine learning (ML) for analyzing heterogeneous treatment effects (HTE) are...

Of Lyme disease and machine learning in a One Health world.

OBJECTIVE: Lyme disease is a vector-borne emerging zoonosis in Ontario driven by human population gr...

MedFuseNet: fusing local and global deep feature representations with hybrid attention mechanisms for medical image segmentation.

Medical image segmentation plays a crucial role in addressing emerging healthcare challenges. Althou...

Low-Power and Low-Cost AI Processor With Distributed-Aggregated Classification Architecture for Wearable Epilepsy Seizure Detection.

Wearable devices with continuous monitoring capabilities are critical for the daily detection of epi...

Machine learning-enhanced surface-enhanced spectroscopic detection of polycyclic aromatic hydrocarbons in the human placenta.

The detection and identification of polycyclic aromatic hydrocarbons (PAHs) and their derivatives, p...

Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.

Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use dis...

A prospective real-time transfer learning approach to estimate influenza hospitalizations with limited data.

Accurate, real-time forecasts of influenza hospitalizations would facilitate prospective resource al...

Machine learning predicts selected cat diseases using insurance data amid challenges in interpretability.

OBJECTIVE: To develop models for prediction of the onset of specific diseases in cats using pet insu...

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