Endocrinology

Diabetes

Latest AI and machine learning research in diabetes for healthcare professionals.

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Supervised Machine Learning-Based Models for Predicting Raised Blood Sugar.

Raised blood sugar (hyperglycemia) is considered a strong indicator of prediabetes or diabetes melli...

Optimization of mid-infrared noninvasive blood-glucose prediction model by support vector regression coupled with different spectral features.

Mid-infrared spectral analysis of glucose in subcutaneous interstitial fluid has been widely employe...

Predicting type 2 diabetes via machine learning integration of multiple omics from human pancreatic islets.

Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secr...

Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques.

The study aimed to achieve the following objectives: (1) to perform the fusion of thermal and visibl...

Group-informed attentive framework for enhanced diabetes mellitus progression prediction.

The increasing prevalence of Diabetes Mellitus (DM) as a global health concern highlights the paramo...

Causal prior-embedded physics-informed neural networks and a case study on metformin transport in porous media.

This study introduces a novel approach to transport modelling by integrating experimentally derived ...

Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers.

Type II diabetes mellitus (T2DM) is a rising global health burden due to its rapidly increasing prev...

Diagnostic application in streptozotocin-induced diabetic retinopathy rats: A study based on Raman spectroscopy and machine learning.

Vision impairment caused by diabetic retinopathy (DR) is often irreversible, making early-stage diag...

Which surrogate insulin resistance indices best predict coronary artery disease? A machine learning approach.

BACKGROUND: Various surrogate markers of insulin resistance have been developed, capable of predicti...

Intelligent deep model based on convolutional neural network's and multi-layer perceptron to classify cardiac abnormality in diabetic patients.

The ECG is a crucial tool in the medical field for recording the heartbeat signal over time, aiding ...

A Microvascular Segmentation Network Based on Pyramidal Attention Mechanism.

The precise segmentation of retinal vasculature is crucial for the early screening of various eye di...

Machine-learning-guided recognition of α and β cells from label-free infrared micrographs of living human islets of Langerhans.

Human islets of Langerhans are composed mostly of glucagon-secreting α cells and insulin-secreting β...

Deep learning detection of diabetic retinopathy in Scotland's diabetic eye screening programme.

BACKGROUND/AIMS: Support vector machine-based automated grading (known as iGradingM) has been shown ...

Assessing spectral effectiveness in color fundus photography for deep learning classification of retinopathy of prematurity.

SIGNIFICANCE: Retinopathy of prematurity (ROP) poses a significant global threat to childhood vision...

Diabetic retinopathy screening through artificial intelligence algorithms: A systematic review.

Diabetic retinopathy (DR) poses a significant challenge in diabetes management, with its progression...

Lipids balance as a spectroscopy marker of diabetes. Analysis of FTIR spectra by 2D correlation and machine learning analyses.

The number of people suffering from type 2 diabetes has rapidly increased. Taking into account, that...

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