Endocrinology

Diabetes

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

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A deep learning approach to hard exudates detection and disorganization of retinal inner layers identification on OCT images.

The purpose of the study was to detect Hard Exudates (HE) and classify Disorganization of Retinal In...

Jul 2024 39030181
[OCT biomarkers in diabetic maculopathy and artificial intelligence].

Diabetes mellitus is a chronic disease the microvascular complications of which include diabetic ret...

Jul 2024 39012371
Association between myosteatosis and impaired glucose metabolism: A deep learning whole-body magnetic resonance imaging population phenotyping approach.

BACKGROUND: There is increasing evidence that myosteatosis, which is currently not assessed in clini...

Jul 2024 39009381
Machine learning-based prediction of diabetic patients using blood routine data.

Diabetes stands as one of the most prevalent chronic diseases globally. The conventional methods for...

Jul 2024 39019099
Enhancing Diabetes Management for Older Patients: The Potential Role of ChatGPT.

Artificial intelligence (AI) technology has the potential to improve diabetes education for older in...

Jul 2024 39009556
Screening for diabetic retinopathy with artificial intelligence: a real world evaluation.

AIM: Periodic screening for diabetic retinopathy (DR) is effective for preventing blindness. Artific...

Jul 2024 38995312
The impact of machine learning on the prediction of diabetic foot ulcers - A systematic review.

INTRODUCTION: Globally, diabetes mellitus poses a significant health challenge as well as the associ...

Jul 2024 39019690
Smell cancer by machine learning-assisted peptide/MXene bioelectronic array.

Non-invasive detection of tumors is of utmost importance to save lives. Nonetheless, identifying tum...

Jul 2024 39018975
Development of a machine learning-based model for the prediction and progression of diabetic kidney disease: A single centred retrospective study.

BACKGROUND: Diabetic kidney disease (DKD) is a diabetic microvascular complication often characteriz...

Jul 2024 39003788
A hybrid model for the detection of retinal disorders using artificial intelligence techniques.

The prevalence of vision impairment is increasing at an alarming rate. The goal of the study was to ...

Jul 2024 38955139
Random survival forest for predicting the combined effects of multiple physiological risk factors on all-cause mortality.

Understanding the combined effects of risk factors on all-cause mortality is crucial for implementin...

Jul 2024 38971926
Estimating the prevalence of diabetic retinopathy in electronic health records with massive missing labels.

OBJECTIVE: The paper aims to address the problem of massive unlabeled patients in electronic health ...

Jul 2024 39717527
Artificial intelligence derived categorizations significantly improve HOMA IR/β indicators: Combating diabetes through cross-interacting drugs.

Improvements in the homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis mod...

Jul 2024 38968766
An automatic deep reinforcement learning bolus calculator for automated insulin delivery systems.

In hybrid automatic insulin delivery (HAID) systems, meal disturbance is compensated by feedforward ...

Jul 2024 38956183
Identification of key biomarkers for early warning of diabetic retinopathy using BP neural network algorithm and hierarchical clustering analysis.

Diabetic retinopathy is one of the most common microangiopathy in diabetes, essentially caused by ab...

Jul 2024 38956257
A deep neural network prediction method for diabetes based on Kendall's correlation coefficient and attention mechanism.

Diabetes is a chronic disease, which is characterized by abnormally high blood sugar levels. It may ...

Jul 2024 38954714
Application of Proteomics and Machine Learning Methods to Study the Pathogenesis of Diabetic Nephropathy and Screen Urinary Biomarkers.

Diabetic nephropathy (DN) has become the main cause of end-stage renal disease worldwide, causing si...

Jul 2024 38949094
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