Public Health & Policy

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

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Showing 3541-3560 of 11,066 articles

Cutaneous leishmaniasis in Casablanca-Settat region (Morocco): spatio-temporal analysis of disease dynamic and machine learning based case prediction

Cutaneous leishmaniasis (CL) caused by Leishmania protozoa and transmitted through infected sandfly bites, poses a significant public health burden in Morocco. Our research aims to retrospectively assess spatio-temporal patterns of CL in the most densely populated region of the country, Casablanca-Settat, during a period of 14 years (2009–2022). We investigate epidemiological trends, seasonal fluc...

A Claims-Based Machine Learning Classifier of Modified Rankin Scale in Acute Ischemic Stroke

We developed a classifier to infer acute ischemic stroke (AIS) severity from Medicare claims using the Modified Rankin Scale (mRS) at discharge. The classifier can be utilized to improve stroke outcomes research and support the development of national surveillance tools. This was a multistate study included all participating centers in the Paul Coverdell National Acute Stroke Program (PCNASP) data...

Natural language processing for scalable feature engineering and ultra-high-dimensional confounding adjustment in healthcare database studies

To improve confounding control in healthcare database studies, data-driven algorithms may empirically identify and adjust for large numbers of pre-exp...

CONORM: Context-Aware Entity Normalization for Adverse Drug Event Detection

Adverse drug events (ADEs) are a critical aspect of patient safety and pharmacovigilance, with significant implications for patient outcomes and publi...

Exploring multidrug resistance patterns in community-acquired E. coli urinary tract infections with machine learning

While associations of antibiotic resistance traits are not random in multidrug-resistant (MDR) bacteria, clinically relevant resistance patterns remai...

Projecting climate change impacts on inter-epidemic risk of Rift Valley fever across East Africa

Rift Valley fever (RVF) is a zoonotic disease that causes sporadic, multi-country epidemics. However, RVF virus (RVFV) also circulates during inter-ep...

Automatic time in bed detection from hip-worn accelerometers for large epidemiological studies: The Tromsø Study

Accelerometers are frequently used to assess physical activity in large epidemiological studies. They can monitor movement patterns and cycles over se...

Foundation time series models for forecasting and policy evaluation in infectious disease epidemics

Epidemic forecasting and policy evaluation rely on mathematical models to predict infectious disease trends and assess the impact of public health pol...

Development and Application of Natural Language Processing on Unstructured Data in Hypertension: A Scoping Review

Hypertension is a global health concern with a vast body of unstructured data, such as clinical notes, diagnosis reports, and discharge summaries, tha...

Data-Driven Insights on Opioid Use and Health Behavior Trends Following Decriminalization: Zero-Shot Sentiment and Behavior Analysis

Opioid decriminalization has taken on renewed urgency in regions grappling with high mortality and health-care costs. Traditional assessments often fo...

Designing a Substance Misuse Data Dashboard for Overdose Fatality Review Teams

Overdose Fatality Review (OFR) is a public health process in which cases of fatal overdose are carefully reviewed to identify prevention strategies. C...

Expanding cholera serosurveillance to vaccinated populations

Mass oral cholera vaccination campaigns targeted at subnational areas with high incidence are central to global cholera elimination efforts. Serologic...

Pancreatic cancer risk prediction using deep sequential modeling of longitudinal diagnostic and medication records

Pancreatic ductal adenocarcinoma (PDAC) is a rare, aggressive cancer often diagnosed late with low survival rates, due to the lack of population-wide ...

Evaluating biomedical feature fusion on machine learning’s predictability and interpretability of COVID-19 severity types

Accurately differentiating severe from non-severe COVID-19 clinical types is critical for the healthcare system to optimize workflow. Current techniqu...

Unraveling the drivers of leptospirosis risk in Thailand using machine learning

Leptospirosis poses a significant public health challenge in Thailand, driven by a complex mix of environmental and socioeconomic factors. This study ...

Mining Social Media Data for Influenza Vaccine Effectiveness Using a Large Language Model and Chain-of-Thought Prompting

Influenza vaccine effectiveness (VE) estimation plays a critical role in public health decision-making by quantifying the real-world impact of vaccina...

Transport-based transfer learning on Electronic Health Records: Application to detection of treatment disparities

Electronic Health Records (EHRs) sampled from different populations can introduce unwanted bi-ases, limit individual-level data sharing, and make the ...

Theory of Mind Imitation by LLMs for Physician-Like Human Evaluation

Aligning the Theory of Mind (ToM) capabilities of Large Language Models (LLMs) with human cognitive processes enables them to imitate physician behavi...

The epidemiology of pathogens with pandemic potential: A review of key parameters and clustering analysis

In the light of the COVID-19 pandemic many countries are trying to widen their pandemic planning from its traditional focus on influenza. However, it ...

Artificial Intelligence-Powered Precision Medicine for Cardiovascular Disease Prevention and Management

Artificial intelligence (AI) is transforming precision medicine, particularly in cardiovascular disease prevention and management. This bibliometric a...

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