Public Health & Policy

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

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Research on runoff process vectorization and integration of deep learning algorithms for flood forecasting.

Accurate multi-step ahead flood forecasting is crucial for flood prevention and mitigation efforts a...

Optimizing large language models in digestive disease: strategies and challenges to improve clinical outcomes.

Large Language Models (LLMs) are transformer-based neural networks with billions of parameters train...

Navigating the future: machine learning's role in revolutionizing antimicrobial stewardship and infection prevention and control.

PURPOSE OF REVIEW: This review examines the current state and future prospects of machine learning (...

Automated machine learning for predicting liver metastasis in patients with gastrointestinal stromal tumor: a SEER-based analysis.

Gastrointestinal stromal tumors (GISTs) are a rare type of tumor that can develop liver metastasis (...

Automated Endoscopic Diagnosis in IBD: The Emerging Role of Artificial Intelligence.

The emerging role of artificial intelligence (AI) in automated endoscopic diagnosis represents a sig...

Fog-based deep learning framework for real-time pandemic screening in smart cities from multi-site tomographies.

The quick proliferation of pandemic diseases has been imposing many concerns on the international he...

Early diagnosis of persons with von Willebrand disease using a machine learning algorithm and real-world data.

BACKGROUND: Von Willebrand disease (VWD) is underdiagnosed, often delaying treatment. VWD claims cod...

Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?

PURPOSE OF REVIEW: This review evaluates how Artificial Intelligence (AI) enhances atherosclerotic c...

Socio-demographic predictors of not having private dental insurance coverage: machine-learning algorithms may help identify the disadvantaged.

BACKGROUND: For accessing dental care in Canada, approximately 62% of the population has employment-...

Machine Learning-Driven Analysis of Individualized Treatment Effects Comparing Buprenorphine and Naltrexone in Opioid Use Disorder Relapse Prevention.

OBJECTIVE: A trial comparing extended-release naltrexone and sublingual buprenorphine-naloxone demon...

A Novel Deep Learning Approach for Forecasting Myocardial Infarction Occurrences with Time Series Patient Data.

Myocardial Infarction (MI) commonly referred to as a heart attack, results from the abrupt obstructi...

Prediction of adolescent weight status by machine learning: a population-based study.

BACKGROUND: Adolescent weight problems have become a growing public health concern, making early pre...

The Surgical Clerkship in the COVID Era: A Natural Language Processing and Thematic Analysis.

INTRODUCTION: Responses to COVID-19 within medical education prompted significant changes to the sur...

Effectiveness of artificial intelligence vs. human coaching in diabetes prevention: a study protocol for a randomized controlled trial.

BACKGROUND: Prediabetes is a highly prevalent condition that heralds an increased risk of progressio...

Predicting malaria outbreak in The Gambia using machine learning techniques.

Malaria is the most common cause of death among the parasitic diseases. Malaria continues to pose a ...

Artificial Intelligence for Urology Research: The Holy Grail of Data Science or Pandora's Box of Misinformation?

Artificial intelligence tools such as the large language models (LLMs) Bard and ChatGPT have genera...

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