Primary Care

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

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Forecasting left ventricular systolic dysfunction in heart failure with artificial intelligence

Objective assessment of left ventricular function remains a key prognosticator that is used to guide therapeutic decisions for patients with heart failure (HF). However, the left ventricular ejection fraction (LVEF) is dynamic, with worsening LVEF linked to increased morbidity and mortality. Identifying patients at risk of LVEF decline would improve prognostication and enable timely therapeutic in...

BeatAI: BiomEtrics for Atrial Arrhythmia Tracking Using Artificial Intelligence

Postoperative atrial fibrillation (POAF) affects 20 to 50% of patients undergoing cardiac surgery and is associated with longer hospital stays and adverse outcomes. Although several risk factors for developing POAF have been identified, accurate prediction remains challenging. Wearable ECG patches and remote patient monitoring enable continuous heart rhythm surveillance. Using AI models, subtle ye...

Scalable screening for emergency department missed opportunities for diagnosis using sequential eTriggers and large language models

Missed opportunities for diagnosis (MODs), sometimes termed diagnostic errors, are a major cause of patient morbidity and mortality in the emergency d...

Childhood Maltreatment and Risk for Illicit Substance Use: Evidence for Mid-Adolescence as a Sensitive Exposure Period

Childhood maltreatment is a well-established risk factor for substance misuse. However, it remains unclear whether risk for specific illicit substance...

Development of Self-Assessment Tools for Osteoporosis among Postmenopausal Vietnamese Women: A Machine Learning Approach

Osteoporosis is a major health concern in Vietnam due to a rise in aging rates. However, cost-effective early screening tools tailored to the Vietname...

Body composition and melanoma incidence risk: insights from a longitudinal lung cancer screening cohort

This study explored the association between low-dose computed tomography (LDCT)-derived body composition and melanoma incidence risk. LDCT scans from ...

Development of Machine Learning Models to Predict Hypoglycemia and Hyperglycemia on Days of Hemodialysis in Patients with Diabetes based on Continuous Glucose Monitoring

Patients with diabetes undergoing hemodialysis (HD) are at risk of asymptomatic hypo- and hypergly-cemia within 24 hours of dialysis. Continuous gluco...

Morphological and Functional Alterations in Type 2 Diabetes Pancreata assessed with MRI-based metrics and [18F]FP-(+)-DTBZ PET

To determine if combining PET-derived beta-cell mass (BCM) estimates with MRI- based morphology metrics improves the prediction of beta-cell functiona...

Multimodal AI for Precision Preventive Cardiology

Coronary artery disease (CAD) is the leading cause of death worldwide, yet it is highly preventable. Early detection is critical, particularly because...

Dietary Macronutrient Intake and the Gut Microbiome in Adults Undergoing Bariatric Surgery for Obesity

Limited information linking dietary intake to gut metagenomic data in bariatric surgery patients is available. We examined whether there were correlat...

Application of Large Language Models (LLM) for Automatic Classification of Work Accident Text Data: Verification of Accuracy and Practicality

Falls are the most frequent type of occupational accident, making the development of effective countermeasures an urgent issue. Traditional accident a...

Identification and validation of tolerogenic dendritic cells-related biomarkers in diabetic retinopathy

Diabetic retinopathy (DR) is a primary microvascular complication of diabetes. Its pathogenesis is associated with chronic inflammation and immune res...

TARGET-AI: a foundational approach for the targeted deployment of artificial intelligence electrocardiography in the electronic health record

Artificial intelligence (AI) applied to routine electrocardiograms (ECGs) offers promise for screening of structural heart disease (SHD), yet broad cl...

Reinforcement learning optimization of automated insulin delivery in type 1 and type 2 diabetes mellitus

Closed-loop insulin delivery systems have proven effective in regulating blood glucose (BG) concentration, thereby reducing the burden of self-care in...

Foundation model embeddings enable cardiovascular screening for people living with HIV in Vietnam using wearable signals

Cardiovascular disease (CVD) screening faces significant challenges in resource-limited settings, where infrastructure and computational constraints p...

Combination AI-Machine Learning to Diagnose Pulmonary Hypertension: A Real-World Evidence Cohort Study

Pulmonary hypertension (PH) is a highly morbid disease, but underdiagnosis is common outside of expert referral centers. Consequentially, there may be...

Individualized Therapy Optimization for Type 2 Diabetes

Type 2 diabetes is a wide-spread chronic condition in which blood glucose and body weight management constitute essential therapeutic targets. Emergin...

Prospective Evaluation of AI Risk Stratification for Triaging Expedited Screening Mammogram Interpretation

To prospectively evaluate the feasibility and performance of expedited screening mammogram interpretation for women identified as high-risk by a deep ...

Understanding the Relationship Between Germ Layer Origin and Cancer Therapy Response: A Systematic Review

Cancer therapeutic response patterns may be fundamentally influenced by embryonic germ layer origin. Emerging evidence suggests mesoderm-derived malig...

A machine learning model to support the screening for methods guidance articles in MEDLINE: A performance evaluation of ASReview simulation mode

Advances in clinical research methods are frequently published in biomedical journals, but identifying these articles remains challenging due to their...

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