Latest AI and machine learning research in endocrinology for healthcare professionals.
UNLABELLED: WGCNA was used to identify DR-related PANoptosis genes, and the LASSO, SVM-RFE, and Random Forest machine learning models were then employed to identify key PANoptosis-related genes. The lncRNA-miRNA-TLR3 networks were constructed, and the levels of hub lncRNAs, hub miRNAs and TLR3 were measured in a high-glucose cell model. The luciferase reporter assay was employed to validate the in...
Diabetic Retinopathy (DR), a leading cause of preventable blindness worldwide, underscores the urgent need for robust AI-driven diagnostic tools. Although various deep learning models for retinal imaging have emerged, their evaluation remains constrained by limited public available datasets that lack both large-scale coverage and fine-grained annotations, compromising reliable assessments of model...
BACKGROUND: Obesity is a major health concern linked to chronic conditions such as diabetes and cardiovascular disease. However, most neurological stu...
Accurate preoperative diagnosis of thyroid nodules via fine-needle aspiration (FNA) biopsy remains challenging, particularly in cases with indetermina...
Bone degeneration diseases, such as osteoporosis, are skeletal disorders characterized by diminished bone mass and increased susceptibility to fractur...
As in many areas of medicine, increasing digitalisation is also having an impact on everyday practice in internal medicine, entailing both enormous po...
BACKGROUND: Diabetes is a chronic condition requiring long-term management, and continuous health education is vital for improving disease awareness a...
Magnetic resonance imaging (MRI) is hard to categorize properly in terms of interclass similarity, there is data imbalance, and sensitive clinical dec...
BACKGROUND: The prevalence of Peripheral Artery Disease (PAD) is rising globally, yet early risk stratification remains challenging due to the limitat...
AIMS: Despite the proven efficacy of GLP-1 receptor agonists (GLP-1 RAs), many patients with type 2 diabetes (T2DM) are not able to achieve glycaemic ...
PURPOSE: Diabetic retinopathy (DR) is a leading cause of blindness in the working-age population. Screening is essential to identify and treat sight-t...
Quantitative analysis of skeletal muscle (SM) and visceral adipose tissue (VAT) cross-sectional volumes at the third lumbar vertebral level (L3) on ab...
BACKGROUND: Type 2 diabetes mellitus (T2D) is a rapidly growing global health concern requiring innovative treatment methods. Ozempic (semaglutide), a...
Maintaining optimal health and preventing diabetes-related complications require accurate and timely monitoring of blood glucose levels. In this conte...
Diabetic Retinopathy (DR) is a major cause of vision loss and blindness in diabetic individuals. DR is conventionally diagnosed by assessing retinal l...
PURPOSE: To determine the diagnostic accuracy and reliability of artificial intelligence (AI) in identifying diabetic retinopathy (DR) and macular oed...
SIGNIFICANCE: This systematic review comprehensively synthesises the progress of artificial intelligence in the grading diagnosis of diabetes-related ...
BACKGROUND AND AIMS: Conventional biomarkers such as low-density lipoprotein (LDL) and high-density lipoprotein may fail to identify patients' risk fo...
A panel of experts in the use of continuous glucose monitoring (CGM) data in the treatment of diabetes met in Burlingame, California on October 27, 20...