Primary Care

Perspective: Depression in Persons with Parkinson's Disease.

Depression is a prevalent and disabling syndrome characterized by sustained sadness and/or anhedonia, as well as cognitive and physical symptoms. In Parkinson's disease (PD), depression is both common and clinically challenging due to overlapping symptoms and complex etiologic interactions. Major depressive disorder occurs in approximately 17% of PD patients, while clinically significant depressiv...

Artificial intelligence in pediatric endocrinology: clinical applications, governance, and future directions.

PURPOSE OF REVIEW: Artificial intelligence has transitioned from theoretical promise to practical implementation across medicine including pediatric endocrinology. This review examines artificial intelligence applications across diabetes care, obesity management, thyroid disorders, growth and puberty, and bone age assessment followed by discussion of limitations and future directions. RECENT FINDI...

Discovery of WRN helicase inhibitors by 3D-CNN docking and ML consensus from traditional Chinese medicine monomers.

The Werner syndrome (WRN) helicase is a validated synthetic-lethal vulnerability in cancers with microsatellite instability (MSI), making WRN inhibiti...

Smartphone-based digital phenotyping for detection of high-risk depression and anxiety in Korean community settings.

BACKGROUND: Smartphones generate continuous behavioral signals such as mobility and activity patterns, offering scalable opportunities for monitoring ...

The oral-gut microbiome axis in diabetes mellitus: a systematic review and emerging clinical perspectives.

Emerging evidence suggests that diabetes mellitus (DM) is not only a metabolic disorder but also a mucosal disease shaped by microbial interactions ac...

Forecasting migraine with time-series machine learning from mobile health data.

BACKGROUND: Machine learning provides a powerful framework to model the complex patterns underlying migraine attack onset from real-world high dimensi...

Artificial Intelligence as an Add-On Instrument in Fetal Ultrasound; Sonographers' and Obstetricians' Expectations.

OBJECTIVE: Artificial intelligence applications (AIA) in fetal ultrasound are rapidly evolving, yet their integration into routine clinical practice r...

Artificial Intelligence in Diabetes Care.

BACKGROUND: Diabetes care requires frequent and high-stakes decisions that must be made in the setting of substantial day-to-day physiologic variabili...

Machine Learning-driven Prioritisation of Lipoprotein(a) Testing: Model Development and Validation.

AIMS: Elevated lipoprotein(a) [Lp(a)] is a common risk factor for cardiovascular disease (CVD) affecting ∼1.4 billion people globally, with novel trea...

Radiomics-Based Classification of Pathological Patterns in Common Carotid Artery Wall.

OBJECTIVES: Abnormal echogenic patterns such as the triple signal pattern can be identified in the common carotid artery (CCA) using ultrasound. These...

Deep learning-assisted otoscopic screening for paediatric otitis media: feasibility of edge deployment.

BACKGROUND: Otitis media is common in children. Otoscopic differentiation of acute otitis media (AOM), otitis media with effusion (OME) and normal tym...

Polygenic and polysocial risk scores in post-type 2 diabetes dementia: Risk stratification and predictive modeling in the UK Biobank cohort.

BackgroundDementia is a common complication of type 2 diabetes mellitus (T2DM), influenced by both genetic susceptibility and social disadvantages. Wh...

[Geriatric oncology patients at the center of nurse-led delirium management].

BACKGROUND: Postoperative delirium is an acute, fluctuating neurocognitive syndrome. It is among the most common perioperative complications in older ...

Development of a multimodal obstructive sleep apnea diagnostic prediction model using two-dimensional facial images and clinical data.

Obstructive sleep apnea (OSA) is a prevalent disorder in middle-aged and obese men with increased risk of cardiovascular disease, metabolic dysfunctio...

Viewpoint on the Consequences and Mitigation of Cognitive Bias in the Radiological Interpretation of Breast Cancer Imaging Using Artificial Intelligence.

Artificial intelligence (AI) is increasingly integrated into breast imaging workflows, offering the potential to enhance diagnostic accuracy, efficien...

Artificial Intelligence Tools for Automating Evidence Synthesis: Scoping Review.

BACKGROUND: Rapidly and accurately synthesizing large volumes of evidence is a time- and resource-intensive process. Once published, reviews often ris...

A Wavelet AI Algorithm to Automatically Identify Postprandial Glucose Responses From Continuous Glucose Monitoring Profiles in People Without Diabetes.

BACKGROUND: Automated identification of postprandial glucose responses (PPGR) from continuous glucose monitoring (CGM) profiles may detect early dysgl...

A Deep Learning Prognostic Model for Diabetes Patients Using Bilateral Fundus Imaging.

AIMS: Diabetes mellitus shortens life expectancy, driven primarily by premature mortality from vascular complications. Mortality models for intensive ...

Mesenchymal stem cell-derived extracellular vesicles in the treatment of type 2 diabetes and its complications: current progress and future directions.

Type 2 diabetes (T2D) and its complications represent a complex disorder involving multiple pathophysiological processes. Although conventional therap...

Artificial intelligence-enabled flexible surface-enhanced Raman scattering substrate based on silver nanoparticles/polypyrrole/chitosan film for sensitive uric acid detection in saliva, serum and urine.

Selective detection of uric acid (UA), a key biomarker associated with cardiovascular diseases, gout and preeclampsia, is important for preventive hea...