Primary Care

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

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Clinical Validation and Machine Learning Optimization of MyCog: A Self-Administered Cognitive Screener for Primary Care Settings

Primary care presents an ideal opportunity for early detection of cognitive impairment, yet primary care clinics face barriers to cognitive screening. MyCog, an EHR-integrated tablet app that is self-administered during the rooming process of a primary care visit, streamlines the screening process to reduce barriers and encourage broader screening. We compared MyCog performance from 65 adults with...

Integrative Machine Learning Approach to Risk Prediction for Dementia and Alzheimer’s Disease

Dementia, especially Alzheimer’s disease (AD), is a major global health challenge marked by progressive cognitive impairment, behavioral changes, and loss of autonomy. As global life expectancy rises, there is a growing urgency for earlier diagnosis and better clinical guidance for AD and other dementia subtypes. This study aimed to develop and evaluate machine learning (ML) models for predicting ...

Regulatory risk loci link disrupted androgen response to pathophysiology of Polycystic Ovary Syndrome

A major challenge in deciphering the complex genetic landscape of Polycystic Ovary Syndrome (PCOS) lies in the limited understanding of how susceptibi...

Prediction of Cardiovascular and Renal Complications of Diabetes by a multi-Polygenic Risk Score in Different Ethnic Groups

We developed a multi-Polygenic risk score (multiPRS) to predict the risk of nephropathy, stroke, and myocardial infarction in people with type 2 diabe...

Target Trial Emulation Applications in Hypertension Research: A Scoping Review

Target Trial Emulation (TTE) has emerged as a rigorous framework for causal inference using observational data, but its application in hypertension re...

Assessing Large Language Model Utility and Limitations in Diabetes Education: A Cross-Sectional Study of Patient Interactions and Specialist Evaluations

To assess the value of an AI-powered conversational agent in supporting diabetes self-management among adults with diabetic retinopathy and limited ed...

Artificial Intelligence for Pre-Anaemic Iron Deficiency Detection Using Rich Complete Blood Count Data

Iron deficiency (ID) is a major contributor to global disease burden and the leading cause of anaemia. Early detection is important for proactive mana...

Barriers and Facilitators to the Implementation of Artificial Intelligence Enabled Diabetes Interventions in Lower-Middle-Income Countries: A Systematic Review Protocol

Diabetes represents an emerging global health crisis, with lower-middle-income countries experiencing a fast growth in prevalence. Diabetes care in th...

Artificial Intelligence-Driven Innovations in Diabetes Care and Monitoring

This study explores Artificial Intelligence (AI)’s transformative role in diabetes care and monitoring, focusing on innovations that optimize patient ...

Artificial Intelligence for Early Detection and Prognosis Prediction of Diabetic Retinopathy

This review explores the transformative role of artificial intelligence (AI) in the early detection and prognosis prediction of diabetic retinopathy (...

Exploring Novel Biomarkers for Early Detection of Osteoporosis

Osteoporosis is characterized by diminished BMD and deteriorated bone microstructure, significantly increasing fracture susceptibility. This study lev...

Can we detect the undetected? Comparing the prodromes of individuals with first episode psychosis detected and undetected by clinical high risk for psychosis services: an electronic health record study

The majority of first episode psychosis (FEP) patients are undetected (DET-) by clinical high risk for psychosis (CHR-P) services prior to onset and t...

Machine Learning Analysis of Electronic Health Records Identifies Interstitial Lung Disease and Predicts Mortality in Patients with Systemic Sclerosis

Interstitial lung disease (ILD) is the leading cause of death in patients with systemic sclerosis (SSc), affecting more than 40% of this population. D...

M-PreSS: A Model Pre-training Approach for Study Screening in Systematic Reviews

Conducting a systematic review is labour-intensive and time-consuming, especially during the study screening process. Previous research has introduced...

Enhancing Fairness in Diabetes Prediction Systems through Smart User Interface Design

Artificial intelligence (AI) in chronic disease prediction often exhibits algorithmic biases, hindering equitable healthcare delivery. This study aims...

Gaps in Artificial Intelligence Research for Rural Health in the United States: A Scoping Review

Artificial intelligence (AI) has impacted healthcare at urban and academic medical centers globally. The current focus on AI deployments in urban area...

DWI and Clinical Characteristics Correlations in Acute Ischemic Stroke After Thrombolysis

Magnetic Resonance Diffusion-Weighted Imaging (DWI) is a crucial tool for diagnosing acute ischemic stroke, yet some patients present as DWI-negative....

AI-Derived Splenic Response in Cardiac PET Predicts Mortality: A Multi-Site Study

Inadequate pharmacologic stress may limit the diagnostic and prognostic accuracy of myocardial perfusion imaging (MPI). The splenic ratio (SR), a meas...

Data-driven discovery of core sleep biomarkers for predicting early cardiometabolic risk in a healthy population using machine learning

Identifying robust biomarkers for future cardiometabolic risk within the crucial “ preventive window” in healthy individuals remains a major challenge...

Modeling the Impact of Social Determinants on Breast Cancer Screening: A Data-Driven Approach

This study addresses the critical implementation science challenge of operationalizing social determinants of health (SDoH) in clinical practice. We d...

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