Diabetes

Diabetes knowledge in young adults: associations with hemoglobin A1C.

The purpose of this study was to quantify associations between hemoglobin A1C (A1C) and diabetes knowledge score using an assessment tool developed to evaluate the level of diabetes knowledge in young adults with Type 1 diabetes (T1DM) and their parent/primary caregiver. Seventy-five participants with T1DM, ages 15-22 years, completed questionnaires. Two 25-item questionnaires were developed: one ...

Noninvasive blood glucose sensing using near infra-red spectroscopy and artificial neural networks based on inverse delayed function model of neuron.

In this paper, a non-invasive blood glucose sensing system is presented using near infra-red(NIR) spectroscopy. The signal from the NIR optodes is processed using artificial neural networks (ANN) to estimate the glucose level in blood. In order to obtain accurate values of the synaptic weights of the ANN, inverse delayed (ID) function model of neuron has been used. The ANN model has been implement...

The Impact of Oversampling with SMOTE on the Performance of 3 Classifiers in Prediction of Type 2 Diabetes.

OBJECTIVE: To evaluate the impact of the synthetic minority oversampling technique (SMOTE) on the performance of probabilistic neural network (PNN), n...

Analysis of underlying causes of inter-expert disagreement in retinopathy of prematurity diagnosis. Application of machine learning principles.

OBJECTIVE: Inter-expert variability in image-based clinical diagnosis has been demonstrated in many diseases including retinopathy of prematurity (ROP...

Computer-aided diagnosis from weak supervision: a benchmarking study.

Supervised machine learning is a powerful tool frequently used in computer-aided diagnosis (CAD) applications. The bottleneck of this technique is its...

Hypoglycemia prediction using machine learning models for patients with type 2 diabetes.

Minimizing the occurrence of hypoglycemia in patients with type 2 diabetes is a challenging task since these patients typically check only 1 to 2 self...

Immediate repair of an incompletely transected obturator nerve during robotic-assisted pelvic lymphadenectomy.

Intraoperative injury of the obturator nerve may occur in gynecologic oncologic procedures when extensive pelvic side wall dissection is performed. In...

Ocular complications in robotic-assisted prostatectomy: a review of pathophysiology and prevention.

Ocular complications reported after robotic-assisted laparoscopic radical prostatectomy (RALP) include corneal abrasion and ischemic optic neuropathy....

Rule extraction from support vector machines using ensemble learning approach: an application for diagnosis of diabetes.

Diabetes mellitus is a chronic disease and a worldwide public health challenge. It has been shown that 50-80% proportion of T2DM is undiagnosed. In th...

A Multi-Agent Large Language Model Reasoning Engine for Early Detection of Pediatric Growth Disorders

Routine childhood growth surveillance is a cornerstone of pediatric care. Growth pattern abnormalities are often early manifestations of chronic disea...

Explainable Diabetic Retinopathy Classification Using Vision Foundation Models

Diabetic retinopathy (DR) is a major cause of preventable blindness, creating a need for accurate and trustworthy automated screening. This study inve...

Domain-Specific Self-Supervised Representation Learning for Retinal Fundus Classification

Despite the growing number of public datasets, annotated medical images remain scarce. Supervised learning methods achieve strong performance on many ...

Automated 2D and 3D Segmentation of AMD and DME Lesions in OCT

Age-related macular degeneration (AMD) and diabetic macular edema (DME) are leading causes of vision loss, and optical coherence tomography (OCT) is t...

A Structural FHMM for Interpretable Disease Trajectories in T2DM

In this work, we propose a structural variant of the Factorial Hidden Markov Model (FHMM) for the analysis of disease trajectories in patients with Ty...

Glucagon-like peptide-1 receptor agonist initiation and risk of clinically recorded Alzheimer's disease-type dementia in older adults with type 2 diabetes: a target trial emulation using causal machine learning

Background Glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 (SGLT2) inhibitors are increasingly used for type 2 di...

Primal--Dual Alternating Neural Learning for Timely Classification with Performance Guarantees

Timely risk classification is essential in many clinical monitoring settings, where decisions must balance the benefit of classifying patients early f...

Causal Modeling of Adverse Pregnancy Outcomes via Adaptive LLM Proposals

Adverse Pregnancy Outcomes (APOs) such as preterm birth and gestational diabetes can have long-term consequences for both the mother and child, yet an...

Curriculum-Aware Interpolate-then-Refine: Learned Physiological Time-Series Imputation under Realistic Missingness

Imputing physiological time series (arterial blood pressure, blood glucose, etc.) is essential for addressing the missingness that pervades clinical d...

Beyond Predictive Fairness: Quantifying Attribution Consistency Across Demographic Groups in Diabetic Retinopathy Screening

Fairness in medical imaging is commonly evaluated through subgroup performance metrics, yet it remains unclear whether models rely on consistent visua...

How to Demonstrate the Glucose Specificity of a Non-Invasive CGM: A Case Study of the SKAMo-2 Clinical Trial and Neogly™

Abstract Background: Every non-invasive continuous glucose monitoring (NI-CGM) technology introduced into the landscape faces the same skeptical quest...