Diabetes

UC-stack: a deep learning computer automatic detection system for diabetic retinopathy classification.

. The existing diagnostic paradigm for diabetic retinopathy (DR) greatly relies on subjective assessments by medical practitioners utilizing optical imaging, introducing susceptibility to individual interpretation. This work presents a novel system for the early detection and grading of DR, providing an automated alternative to the manual examination.. First, we use advanced image preprocessing te...

Study of Serum Fibroblast Growth Factor 23 as a Predictor of Endothelial Dysfunction among Egyptian Patients with Diabetic Kidney Disease.

Endothelial dysfunction in patients with diabetic nephropathy is caused by nontraditional factors in addition to common risk factors (e.g., hypertension) in people with normal kidney function. These nontraditional factors include factors involved in mineral bone disease in these patients. One of these factors is fibroblast growth factor 23 (FGF-23). We aimed to evaluate the relationship between fl...

What is meant by 'integrated personalized diabetes management': A view into the future and what success should look like.

Integrated personalized diabetes management (IPDM) has emerged as a promising approach to improving outcomes in patients with diabetes mellitus (DM). ...

How Socio-economic Inequalities Cluster People with Diabetes in Malaysia: Geographic Evaluation of Area Disparities Using a Non-parameterized Unsupervised Learning Method.

Accurate assessments of epidemiological associations between health outcomes and routinely observed proximal and distal determinants of health are fun...

Identifying Diabetic Retinopathy in the Human Eye: A Hybrid Approach Based on a Computer-Aided Diagnosis System Combined with Deep Learning.

Diagnosing and screening for diabetic retinopathy is a well-known issue in the biomedical field. A component of computer-aided diagnosis that has adva...

Risk Factors for Development of Diabetes Insipidus and Syndrome of Inappropriate Antidiuretic Hormone Secretion after Transsphenoidal Resection of Pituitary Adenoma.

 We aimed to determine the incidence and risk factors for development of diabetes insipidus (DI) and syndrome of inappropriate antidiuretic hormone s...

Applicable Machine Learning Model for Predicting Contrast-induced Nephropathy Based on Pre-catheterization Variables.

Early inner plexiform layer thinning and retinal nerve fiber layer thickening in excitotoxic retinal injury using deep learning-assisted optical coherence tomography.

Excitotoxicity from the impairment of glutamate uptake constitutes an important mechanism in neurodegenerative diseases such as Alzheimer's, multiple ...

COMPARISON OF C-PEPTIDE LEVELS IN MONOGENIC FORMS OF DIABETES WITH OTHER TYPES OF DIABETES: A SINGLE-CENTER STUDY.

OBJECTIVE: This study aimed to evaluate the utility of C-peptide levels in the differentiation of monogenic forms of diabetes from type 1 diabetes mel...

Validation of a deep learning system for the detection of diabetic retinopathy in Indigenous Australians.

BACKGROUND/AIMS: Deep learning systems (DLSs) for diabetic retinopathy (DR) detection show promising results but can underperform in racial and ethnic...

Protocol for metadata and image collection at diabetic foot ulcer clinics: enabling research in wound analytics and deep learning.

BACKGROUND: The escalating impact of diabetes and its complications, including diabetic foot ulcers (DFUs), presents global challenges in quality of l...

inhibition of biofilm and virulence factor production in azole-resistant strains of isolated from diabetic foot by stabilized tin (IV) oxide nanoparticles.

The advent of nanotechnology has been instrumental in the development of new drugs with novel targets. Recently, metallic nanoparticles have emerged a...

Prescription trend and lactic acidosis in patients prescribed metformin before and after the revision of package insert for allowing metformin administration to patients with moderately decreased kidney function based on real-world data from MID-NET in Japan.

INTRODUCTION: This study was conducted to understand the impact of package insert (PI) revision in Japan on 18 June 2019 to allow metformin use for pa...

Optimization of chemical conditions for metabolites production by using response surface methodology and investigation of antimicrobial as well as anticancer activities.

() is a medicinal mushroom that is known for its ability to produce compounds with physiological effects on human health. This research was undertake...

The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review.

BACKGROUND: Diabetes mellitus (DM) is a major health concern among children with the widespread adoption of advanced technologies. However, concerns a...

Development and application of Chinese medical ontology for diabetes mellitus.

OBJECTIVE: To develop a Chinese Diabetes Mellitus Ontology (CDMO) and explore methods for constructing high-quality Chinese biomedical ontologies.

Efficacy and safety of insulin glargine 300 units/mL vs insulin degludec in patients with type 1 and type 2 diabetes: a systematic review and meta-analysis.

BACKGROUND: Ultra-long-acting insulin analogs [insulin degludec (IDeg) and insulin glargine 300 units/mL (IGla-300)] offer a longer duration of action...

DiaNet v2 deep learning based method for diabetes diagnosis using retinal images.

Diabetes mellitus (DM) is a prevalent chronic metabolic disorder linked to increased morbidity and mortality. With a significant portion of cases rema...

Development and application of an amplified luminescent proximity homogeneous assay-linked immunosorbent assay for the accurate quantification of kidney injury molecule-1.

Kidney injury molecule-1 (Kim-1), a specific marker of kidney injury, is usually not expressed in normal kidneys or at very low levels but is highly ...

Image Analysis-Based Machine Learning for the Diagnosis of Retinopathy of Prematurity: A Meta-analysis and Systematic Review.

TOPIC: To evaluate the performance of machine learning (ML) in the diagnosis of retinopathy of prematurity (ROP) and to assess whether it can be an ef...