Diabetes

Investigating the anti-obesity potential of leaf bioactive compounds through machine learning and computational biology methods.

Obesity, a growing global health concern, is linked to severe ailments such as cardiovascular diseases, type 2 diabetes, cancer, and neuropsychiatric disorders. Conventional pharmacological treatments often have significant side effects, highlighting the need for safer alternatives. Traditional Chinese Medicine (TCM) offers potential solutions, with plant extracts like those from leaves showing p...

Standardized evaluation of diabetic retinopathy using artificial intelligence and its association with metabolic dysfunction-associated steatotic liver disease in Japan: A cross-sectional study.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is common in patients with obesity and diabetes and can lead to serious complications. This study aimed to evaluate fundus photographs using artificial intelligence to explore the relationships between diabetic retinopathy (DR), MASLD, and related factors. In this cross-sectional study, we included 1,736 patients with a history of di...

L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction.

Pre-training strategies based on self-supervised learning (SSL) have demonstrated success as pretext tasks for downstream tasks in computer vision. Ho...

Potential shared mechanisms in atopic dermatitis and type 2 diabetes identified via transcriptomic and machine learning approaches.

Although atopic dermatitis (AD) and type 2 diabetes mellitus (T2DM) may appear clinically and pathophysiologically unrelated, AD is a common skin dise...

Advances in Machine Learning-Aided Thermal Imaging for Early Detection of Diabetic Foot Ulcers: A Review.

The prevention and early warning of foot ulcers are crucial in diabetic care; however, early microvascular lesions are difficult to detect and often d...

Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management.

One of the health challenges in the 21st century is to rethink approaches to non-communicable disease prevention. A solution is a smart city that impl...

Comparative study of alpha-glucosidase inhibition of four Vietnamese medicinal plants , , , and : and studies.

Four medicinal plants , , , and growing in the South of Vietnam were investigated for their alpha-glucosidase inhibition. The crude methanol extract ...

Exploring diabetes through the lens of AI and computer vision: Methods and future prospects.

Early diagnosis and timely initiation of treatment plans for diabetes are crucial for ensuring individuals' well-being. Emerging technologies like art...

Genotype-negative multiple endocrine neoplasia type 1 with prolactinoma, hyperparathyroidism, and subclinical Cushing's syndrome accompanied by hyperglycemia: a case report.

BACKGROUND: Multiple endocrine neoplasia type 1 (MEN1) is a rare autosomal dominant disorder, accompanied by multiple endocrine neoplasms of the parat...

The native Iranian soil bacteria with high potential to produce extracellular methionine gamma-lyase.

This study aimed to screen native methionine gamma-lyase (L-methioninase) producing bacteria from soil samples and optimize the culture media for enha...

Early Detection of Dementia in Populations With Type 2 Diabetes: Predictive Analytics Using Machine Learning Approach.

BACKGROUND: The possible association between diabetes mellitus and dementia has raised concerns, given the observed coincidental occurrences.

Linsitinib inhibits proliferation and induces apoptosis of both IGF-1R and TSH-R expressing cells.

BACKGROUND: The insulin-like growth factor 1 receptor (IGF-1R) and the thyrotropin receptor (TSH-R) are expressed on orbital cells and thyrocytes. The...

Broccoli () leaves exhibit significant antidiabetic potential in alloxan-induced diabetic rats: the putative role of ABC vacuolar transporter for accumulation of Quercetin and Kaempferol.

BACKGROUND: The global prevalence of diabetes among adults over 18 years of age is expected to increase from 10.5% to 12.2% (between 2021 and 2045). P...

Evaluating the efficacy of AI systems in diabetic retinopathy detection: A comparative analysis of Mona DR and IDx-DR.

PURPOSE: To compare two artificial intelligence (AI)-based Automated Diabetic Retinopathy Image Assessment (ARIA) softwares in terms of concordance wi...

Revolutionary drug repositioning: the preventive and therapeutic potential of metformin and other antidiabetic drugs in age-related macular degeneration.

Age-related macular degeneration (AMD) is a leading cause of blindness among the elderly worldwide. Anti-vascular endothelial growth factor (anti-VEGF...

Modeling the fasting blood glucose response to basal insulin adjustment in type 2 diabetes: An explainable machine learning approach on real-world data.

INTRODUCTION: Optimal basal insulin titration for people with type 2 diabetes is vital to effectively reducing the risk of complications. However, a s...

ECLStat: A robust machine learning based visual imaging tool for electrochemiluminescence biosensing.

Visual electrochemiluminescence (ECL) has emerged as a prominent diagnostic method for accurately quantifying various disease markers even at point of...

Classification of glucose-level in deionized water using machine learning models and data pre-processing technique.

Accurate monitoring of glucose levels is essential in the field of diabetes detection and prevention to ensure appropriate treatment planning. Convent...

Machine-learning-based identification of patients with IgA nephropathy using a computerized medical billing database.

The billing database of the universal healthcare system in Japan potentially includes large-cohort data of patients with immunoglobulin A nephropathy,...

Prediction of prolonged mechanical ventilation in the intensive care unit via machine learning: a COVID-19 perspective.

Early recognition of risk factors for prolonged mechanical ventilation (PMV) could allow for early clinical interventions, prevention of secondary com...