Endocrinology

Artificial intelligence in cardio-kidney-metabolic care: Transforming integrated disease management through data-informed innovation.

Artificial intelligence (AI) is rapidly transforming the landscape of chronic medical conditions, such as cardio-kidney-metabolic (CKM) issues linked to type 2 diabetes and obesity. It creates new opportunities to shift from reactive to proactive, data-driven care. Recent advances include predictive algorithms for hypoglycemia and hyperglycemia, decision-support tools for insulin titration, and ge...

Triglyceride-Glucose-Waist-to-Weight Index: Novel Biomarker for Mild Cognitive Impairment in Older People With Sarcopenic Obesity.

BACKGROUND: Sarcopenic obesity (SO) is closely associated with mild cognitive impairment (MCI). However, traditional body composition-based diagnostic criteria for SO fail to adequately incorporate insulin resistance, a key pathophysiological mechanism. This study aimed to investigate the association between SO, defined using multiple diagnostic criteria including novel insulin resistance indices,...

[Artificial intelligence in diabetic retinopathy screening].

INTRODUCTION: Visual impairment and blindness continue to represent a substantial disease burden in Hungary. According to national epidemiological dat...

Guideline Adherence in the Diagnosis of PCOS Among Adolescents: Comparing Obstetricians and Gynecologists With Large Language Models.

STUDY OBJECTIVE: Polycystic ovary syndrome in adolescence is a condition associated with long-term cardiovascular, metabolic, and psychological outcom...

Spatially resolved single cell analysis suggests an APOE NCF1 associated immunosuppressive niche and its prognostic signature in thyroid cancer.

BACKGROUND: Thyroid carcinoma (TC) presents a rising global incidence, with a subset of cases progressing aggressively despite standard therapies. The...

Probiotics and Postbiotics in Life-Style Disease Management: A Comprehensive Review on the Technologies in the Era of Omics and Artificial Intelligence.

Both conventional and next-generation probiotics play a crucial role in maintaining host homeostasis. They modulate insulin sensitivity, immune-regula...

Machine learning and SHAP interpretation for predicting coronary heart disease-diabetes comorbidity with dietary antioxidants.

Coronary heart disease (CHD) and diabetes mellitus frequently co-occur through shared mechanisms such as oxidative stress and inflammation. Whether sp...

Explainable ensemble machine learning for predicting diabetes mellitus and identifying key risk factors: a population-based study in northern Bangladesh.

Diabetes mellitus (DM) is an escalating global public health concern, with a rapidly increasing burden in low- and middle-income countries, including ...

Electronic health record-derived machine learning model for hypoglycemia risk prediction in type 2 diabetes mellitus patients: development and validation.

BACKGROUND: Hypoglycemia is a serious complication of diabetes. Early recognition of hypoglycemia can improve clinical prognosis, however, traditional...

Organoids as next-generation models for investigating intracranial tumours.

Tumour organoids have emerged as important tools in brain tumour research, addressing long-standing limitations of conventional two-dimensional cultur...

Application of construction and validation of logistic regression model in risk prediction of non-proliferative diabetic retinopathy in type 2 diabetes mellitus.

AIMS: Diabetic retinopathy (DR) is a leading cause of vision impairment in type 2 diabetes mellitus (T2DM), with non-proliferative DR (NPDR) represent...

Integration of network pharmacology, deep learning, and molecular biology reveals the efficacy of Citrus aurantium L. var. amara Engl. blossom extract in ameliorating diabetic osteoporosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Diabetic osteoporosis (DOP) is a type of metabolic bone disease. Blossom of Citrus aurantium L. var. amara Engl. (CAVA...

Enhancing brain tumor classification with a simplified CNN through hyperparameter optimization.

Brain tumors remain a major public health challenge because of their high mortality rate and the need for timely and accurate diagnosis. Magnetic Reso...

Personalized non-invasive continuous glucose monitoring via multiparameter-informed machine learning.

Non-invasive continuous glucose monitoring (NCGM) based on reverse iontophoresis (RI) holds considerable promise for diabetes management; however, its...

Capturing multi-disease states on a spectrum with machine learning and routine clinical data.

BACKGROUND: Diseases exist on spectra of risk factors, cellular perturbations, organ dysfunction, and clinical manifestations. It is unknown whether t...

Precision Management of Autoimmune Ocular Complications: Th17 Mechanisms and Therapeutic Innovations.

Precision management of ocular complications in systemic autoimmune diseases, such as Sjögren's syndrome (SS), systemic lupus erythematosus (SLE), Beh...

Early-life proteomic and microbiome features signal obesity risk across 26 years of follow-up.

UNLABELLED: Childhood obesity is rising globally. Yet, few studies have examined the microbiome and proteome in early childhood in relation to this ou...

Predicting late radiation-associated neurocognitive and endocrine toxicity in patients with brain tumors.

PURPOSE: Neurocognitive and endocrine dysfunction are potential complications of cranial irradiation. However, risk factors are poorly understood, imp...

Efficacy of an e-Learning Module on Endocrine Disruptors for Family Medicine Residents: Matched Before-And-After Cohort Study.

BACKGROUND: Environmental factors account for 23% of global deaths and 25% of chronic diseases. In France, the Fourth National Environmental Health Pl...

AI driven Hybrid CNN transformer model for early detection and severity assessment of diabetic retinopathy.

As the major cause of sight impairment in working age adults is diabetic retinopathy (DR) which requires timely and proper diagnosis to avoid the irre...