Latest AI and machine learning research in endocrinology for healthcare professionals.
INTRODUCTION: The identification of non-diabetic kidney disease (NDKD) in diabetic patients is critically important. Unlike diabetic nephropathy, NDKD often requires additional therapeutic interventions beyond standard diabetes care. There is a need to develop computational methods using electronic medical record data to identify NDKD in diabetic patients for whom kidney biopsy is not an option. M...
Diabetic kidney disease (DKD), characterized by progressive renal dysfunction, is a prevalent microvascular complication of diabetes mellitus and a leading cause of end-stage renal disease worldwide. Despite advances in glycemic and blood pressure control, the incidence and prevalence of DKD continue to escalate, posing a growing public health challenge. Extracellular vesicles, particularly exosom...
Approximately 30-50% of Papillary thyroid carcinoma (PTC) patients develop cervical lymph nodes (LNs) metastasis, significantly increasing the risk of...
BackgroundThe impact of deep learning (DL)-based computed tomography (CT) reconstruction on the visualization of distal and collateral arteries in dia...
OBJECTIVE: Management of gestational diabetes mellitus (GDM) largely follows a uniform approach, despite growing recognition of GDM heterogeneity. We ...
CONTEXT: Accurate methimazole (MMI) dose adjustment in pediatric hyperthyroidism is crucial, but individualized titration relies on clinician experien...
CONTEXT: Adiposomes carry bioactive lipids that shape systemic metabolism and vascular function. OBJECTIVE: Building on our previous findings that obe...
Depressive symptoms are common among adults with diabetes and are associated with adverse clinical outcomes, including mortality. Evidence from genera...
Type 2 diabetes mellitus (T2D) is a chronic metabolic disorder characterized by insulin resistance, impaired glucose homeostasis, and low-grade inflam...
Insulin resistance (IR), a primary precursor to type 2 diabetes, is characterized by impaired insulin action in tissues1. However, diagnostic methods ...
Synthetic patient data offer a promising avenue for clinical research, but their usefulness depends on preserving statistical fidelity, biomedical pla...
OBJECTIVE: To evaluate how continuous glucose monitoring (CGM)-derived metrics relate to severe hypoglycemia (SH) events in individuals with type 1 di...
OBJECTIVE: To evaluate whether the Area Deprivation Index (ADI) contributes to predicting type 2 diabetes development in youth with prediabetes compar...
BACKGROUND: Artificial intelligence (AI) is increasingly applied in chronic disease management, including diabetes, where it has the potential to supp...
OBJECTIVE: Prediabetes is a silent condition that often goes undetected. However, timely interventions could prevent its progression to type 2 diabete...
Recent findings from the Honolulu Heart Program cohort in Hawaii suggest a longevity-associated variant of FOXO3 may provide resilience against cardio...
BACKGROUND: Iodine-131 (131I) therapy is a cornerstone of nuclear medicine for thyroid diseases and certain cancers. This review evaluates the transit...
Adrenal incidentalomas are a modern-day problem, which has slowly been met by modern day technological innovations. Further characterization of adrena...
BACKGROUND: Early detection of metabolic dysfunction before diabetes onset remains a critical challenge in preventive medicine. Although glucose dynam...
Type 2 Diabetes Mellitus (T2DM) confers a significant risk for Mild Cognitive Impairment (MCI), yet robust biomarkers for early detection remain limit...