Primary Care

AI in Mental Health: A Review of Technological Advancements and Ethical Issues in Psychiatry.

Artificial intelligence (AI) is transforming digital health, its influence is expanding across multiple sectors, with mental health and psychiatric care emerging as key areas of transformation. While significant advancements have been made in medical AI, there remains a need to better understand how these technologies are integrated into clinical practice and what challenges they introduce. We exa...

A plasma 9-microRNA signature for lung cancer early detection: a multicenter analysis.

Lung cancer remains the leading cause of cancer-related deaths worldwide. Low-dose computed tomography (LD-CT) screening, combined with effective minimally invasive molecular testing such circulating microRNA, has the potential to reduce the burden of lung cancer. However, their clinical application requires further validation, including studies across diverse patient cohorts from different countr...

Bioinformatic Analysis of Complex In Vitro Fertilization Data and Predictive Model Design Based on Machine Learning: The Age Paradox in Reproductive Health.

Since its inception in 1987, in vitro fertilization (IVF) has constituted a significant medical achievement in the field of fertility treatment, offer...

Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization.

Large-cohort imaging and diagnostic studies often assess cardiac function but overlook underlying biological mechanisms. Cardiac digital twins (CDTs) ...

Tools and methods for cataract recognition in low-resource settings: A narrative review.

Cataracts are a leading cause of global blindness, with many low-resource populations having poor access to eye care. While much is known regarding su...

Predicting infections with multidrug-resistant organisms (MDROs) in neurocritical care patients with hospital-acquired pneumonia (HAP): development of a novel multivariate prediction model.

Hospital-acquired pneumonia (HAP) is prevalent in the neuro-intensive care unit (NICU), significantly increasing susceptibility to infections with mul...

Exploring potential diagnostic markers and therapeutic targets for type 2 diabetes mellitus with major depressive disorder through bioinformatics and in vivo experiments.

Type 2 diabetes mellitus (T2DM) and Major depressive disorder (MDD) act as risk factors for each other, and the comorbidity of both significantly incr...

Prediction of Poor Visual Outcomes at Idiopathic Intracranial Hypertension Diagnosis Using a Supervised Machine Learning Algorithm.

BACKGROUND: Idiopathic intracranial hypertension (IIH) is a vision-threatening disorder mainly affecting women of a reproductive age. Prompt diagnosis...

Balancing Act: Generative AI Tools and Scope of Practice in Health Coaching.

This article explores the effects of generative artificial intelligence (genAI) in health coaching, highlighting its potential benefits and ethical c...

Bridging the gap in obesity research: A consensus statement from the European Society for Clinical Investigation.

BACKGROUND: Most forms of obesity are associated with chronic diseases that remain a global public health challenge.

Deciphering Shared Gene Signatures and Immune Infiltration Characteristics Between Gestational Diabetes Mellitus and Preeclampsia by Integrated Bioinformatics Analysis and Machine Learning.

Gestational diabetes mellitus (GDM) and preeclampsia (PE) are common and serious disorders of pregnancy that threaten maternal safety and perinatal ou...

Dual-Mode Detection of Trypsin and Screening of Trypsin Inhibitors on the Basis of a Colorimetric/Fluorescence Sensing Probe.

Trypsin is a specific and reliable diagnostic biomarker of pancreatic function and pathological changes. Thus, detecting trypsin and screening trypsin...

Serum sclerostin as a marker of microvascular and macrovascular complications among children and adolescents with type 1 diabetes mellitus.

BACKGROUND: Uncontrolled diabetes mellitus (DM) accelerates atherosclerosis and vascular diseases, leading to micro- and macrovascular complications. ...

Multi-technique computational assessment of fluoride uptake in enamel using PIGE, NEXAFS, and Raman spectroscopy.

The uptake of fluoride in the enamel matrix is an effective strategy to prevent demineralization and caries formation. In this study a comprehensive m...

Intravascular Lithotripsy Versus Rotational Atherectomy for Calcified Coronary Lesions: A Systematic Review and an Updated Meta-Analysis of Clinical Outcomes.

BACKGROUND: Severe coronary artery calcification (CAC) remains a significant challenge in interventional cardiology, especially in elderly and comorbi...

Semi-quantitative analysis of Right Ventricular Myocardial First-pass Perfusion Using Cardiac Magnetic Resonance Imaging in Systemic Sclerosis and Pulmonary Arterial Hypertension.

BACKGROUND: Right ventricular (RV) myocardial perfusion has been touted as a primary mechanism to understand impairment in RV function in patients wit...

Detection of ESBL-producing complex with VITEK 2 system and screening cutoffs for implementing confirmatory tests.

complex (C) are important nosocomial pathogens that can be reservoirs of transmissible extended-spectrum β-lactamase (ESBL) genes. Therefore, it is e...

Impact of type 2 diabetes mellitus on apical periodontitis size, endotoxin levels and bacterial load in root canals with necrotic pulp.

INTRODUCTION: This clinical study was conducted to describe the endodontic microbiological profile of teeth with apical periodontitis in patients with...

Deep learning-based evaluation of the severity of mitral regurgitation in canine myxomatous mitral valve disease patients using digital stethoscope recordings.

BACKGROUND: Myxomatous mitral valve disease (MMVD) represents the most prevalent cardiac disorder in dogs, frequently resulting in mitral regurgitatio...

Non-proliferative diabetic retinopathy detection using Rosmarus Quagga optimized explainable generative meta learning based deep convolutional neural network model.

PURPOSE: Non-Proliferative Diabetic Retinopathy (NPDR) is a complication of diabetes disease where there is damage of the blood vessels in retina but ...