Primary Care

Development of explainable machine learning-based prediction models of depression with mild and severe insomnia in middle-aged and elderly Chinese people.

BACKGROUND: The risk of depression is significantly elevated in middle-aged and older adults with insomnia; however, the pathways between mild and severe insomnia are different. Most existing prediction tools treat insomnia as a single construct, ignoring its heterogeneity. It is crucial to develop an interpretable, severity-specific modeling framework to quantify depression risk, identify shared ...

Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.

Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalence rising due to aging populations, diabetes, hypertension, and environmental factors. Conventional risk assessment tools such as the CKD Epidemiology Collaboration equation and the Kidney Failure Risk Equation are limited in precision, generalizability, and their ability to identify rapid progresso...

Predicting Heart Failure From 12-Lead ECGs Using AI: A HeartShare/AMP-HF Pooled Cohort Analysis.

BACKGROUND: Artificial intelligence applied to electrocardiograms (ECG-AI) offers a scalable approach to identify individuals at risk for heart failur...

Flavonoid-modulated JAK-STAT signaling mitigates malignant transformation and drug resistance in breast tumors: A clinically relevant 3PM-guided innovation.

BACKGROUND: Breast cancer (BC) treatment efficacy is often compromised by tumor cell plasticity and multidrug resistance of multi-factorial origin. Am...

The Development and Validation of Multivariable Electronic Health Record-Based Models to Predict Diabetic Ketoacidosis-Related Hospitalizations for Adults with Type 1 Diabetes.

AIM: To develop and validate models that use electronic health record (EHR) data to predict diabetic ketoacidosis (DKA)-related hospitalizations over ...

Mapping systemic inter-organ metabolic networks across glycemic continuum using whole-body [18F]FDG PET/CT and machine learning.

PURPOSE: Glucose homeostasis relies on coordinated interactions among multiple organs, and its disruption relates to diabetes development. This study ...

The application of machine learning in the evaluation of urinary tract infections incidence in patients in a Nursing and Treatment Facility.

BACKGROUND: Urinary tract infection (UTI) is a serious problem in the healthcare system. It is caused by bacteria from the gastrointestinal tract. The...

Swallowing Dysfunction in Stroke: The Role of Nurses and Rehabilitation Strategies Across Recovery Phases.

BACKGROUND: Swallowing dysfunction is a common consequence of neurological disorders such as stroke, and may lead to malnutrition, aspiration, and red...

Can artificial intelligence and wearable technologies transform diabetes foot health?

PURPOSE OF REVIEW: Diabetes foot ulcers (DFUs) affect millions globally, and are a global health challenge, contributing significantly to morbidity, m...

Construction and validation of a hypertensive nephropathy diagnostic model based on mitochondrial-related genes using machine learning combined with WGCNA.

BACKGROUND: Hypertensive nephropathy (HTN) arises from chronic hypertension and may potentially result in severe renal failure. Due to the absence of ...

From Cuffs to Code: Machine Learning in Non-Invasive Blood Pressure Monitoring.

Blood pressure (BP) measurement in both acute care and outpatient settings is essential, as conditions like hypertension and hypotension are common an...

Assessing the User Experience of an LLM-Based Conversational Assistant in Diabetes Mellitus Care.

UNLABELLED: This article presents the design, implementation, and evaluation of MarIA, a GPT-3.5-powered virtual assistant integrated into a messaging...

Unraveling Shared Diagnostic Biomarkers: Integrated Bioinformatics Identification of CGB7, MYCNUT, and GPR32 in Gestational Diabetes Mellitus and Retinopathy of Prematurity.

The relationship between Gestational Diabetes Mellitus (GDM) and Retinopathy of Prematurity (ROP) is not fully understood, but both conditions may sha...

MIEF-Net: multimodal image-enhanced fusion network for intelligent fall risk prediction.

Falls among older adults are a major health concern, often resulting in severe injuries and diminished quality of life. Early prediction of fall risk ...

Takotsubo cardiomyopathy: Advances in pathophysiology, diagnostic biomarkers, genetic insights, multisystemic involvement, treatment updates & multidisciplinary interventions.

BACKGROUND: Takotsubo cardiomyopathy (TTC) is an acute, reversible cardiac syndrome triggered by physical or emotional stress, involving complex multi...

Artificial intelligence methods in gestational diabetes mellitus prediction: A systematic literature review.

Gestational diabetes mellitus (GDM) is the most common metabolic disorder in pregnancy, posing risks to both maternal and neonatal health. Artificial ...

Generative artificial intelligence in scientific publishing: Expectations for authors and reviewers at Preventive Medicine and Preventive Medicine Reports.

Artificial intelligence for arterial blood gas interpretation.

Arterial blood gas (ABG) analysis is a fundamental diagnostic tool in clinical medicine, offering critical insights into a patient's respiratory and m...

Using precision medicine methods to identify disease stages for chronic limb-threatening ischemia in participants of the BEST-CLI trial.

BACKGROUND: Chronic limb-threatening ischemia (CLTI), the most severe form of peripheral artery disease, is associated with a high risk of limb loss. ...

Machine learning-assisted characterization of cervid skin tissues with chronic wasting disease by nano-enabled Raman spectroscopic biosensing.

Chronic wasting disease (CWD) is a contagious neurodegenerative disease in cervids and its spread threatens the health of wild and farm-raised animals...