Primary Care

Latest AI and machine learning research in primary care for healthcare professionals.

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Machine Learning Risk Prediction for Prolonged Hospitalization in Frail Older Adults with Multimorbidity

Frailty and multimorbidity are common in older adults and contribute substantially to prolonged hosp...

Artificial Intelligence-Enabled Electrocardiogram for Elevated Left Ventricular Filling Pressure

Left ventricular filling pressure (LVFP) is associated with heart failure symptoms, a key prognostic...

Predicting Amyloid Positivity Through Proteomic and Machine Learning Approaches

Alzheimer’s disease is a progressive neurodegenerative disorder where early detection remains diffic...

Discovering latent subtypes of preterm birth and genetic risk using tensor decomposition on electronic health records

Preterm birth is a syndrome that is triggered by diverse biological pathways and presents with many ...

Clinical Implementation of an AI Algorithm for Substance Misuse Screening in Hospitalized Adults

Manual inpatient screening for substance misuse is labor-intensive and inconsistently applied. Evalu...

PANCDetect: Early Detection of Pancreatic Cancer from Multimodal EHR data with LLM Embeddings

Pancreatic cancer (PANC) is often diagnosed at late stages due to the absence of specific early symp...

A photoplethysmography-based aging clock reveals genetic determinants of arterial aging

Arterial aging, marked by progressive vascular stiffening, is a contributor to cardiovascular diseas...

Circulating Metabolites are Linked to Dementia and Brain Imaging Phenotypes, and Mediate Modifiable Risk Pathways

Dementia poses an escalating global health burden, yet its underlying mechanisms remain incompletely...

Physiological foundation modeling for subclinical disease assessment: a prospective pilot

Clinical studies struggle to locate the right patients, in part because many remain undiagnosed or l...

Causal modeling of chronic kidney disease in a participatory framework for informing the inclusion of social drivers in health algorithms

Incomplete or incorrect causal theories are a key source of bias in machine learning (ML) algorithms...

A MULTI-DIMENSIONAL MACHINE LEARNING APPROACH FOR CARDIOVASCULAR DISEASE PREDICTION IN THE UK BIOBANK STUDY

Cardiovascular diseases (CVD) are complex disorders involving the impaired function of blood vessels...

Discrete-Event Simulation Modeling Framework for Cancer Interventions and Population Health in R (DESCIPHR): An Open-Source Pipeline

Simulation models inform health policy decisions by integrating data from multiple sources and forec...

Sociodemographic Bias in Large Language Model Clinical Trial Screening

Large language models (LLMs) are increasingly used in randomized clinical trial (RCT) screening, but...

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