AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Diabetes Mellitus

Showing 131 to 140 of 411 articles

Clear Filters

Artificial intelligence in diabetes management: Advancements, opportunities, and challenges.

Cell reports. Medicine
The increasing prevalence of diabetes, high avoidable morbidity and mortality due to diabetes and diabetic complications, and related substantial economic burden make diabetes a significant health challenge worldwide. A shortage of diabetes specialis...

An effective correlation-based data modeling framework for automatic diabetes prediction using machine and deep learning techniques.

BMC bioinformatics
The rising risk of diabetes, particularly in emerging countries, highlights the importance of early detection. Manual prediction can be a challenging task, leading to the need for automatic approaches. The major challenge with biomedical datasets is ...

Diagnosis of diabetes mellitus using high frequency ultrasound and convolutional neural network.

Ultrasonics
The incidence of diabetes mellitus has been increasing, prompting the search for non-invasive diagnostic methods. Although current methods exist, these have certain limitations, such as low reliability and accuracy, difficulty in individual patient a...

Can ChatGPT Help in the Awareness of Diabetes?

Annals of biomedical engineering
Diabetes is a common chronic illness that requires continual patient education and support to be effectively managed. The lack of diabetes educators and the limitations of conventional education approaches make it difficult to meet the specific needs...

An advanced deep learning method to detect and classify diabetic retinopathy based on color fundus images.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
BACKGROUND: In this article, we present a computerized system for the analysis and assessment of diabetic retinopathy (DR) based on retinal fundus photographs. DR is a chronic ophthalmic disease and a major reason for blindness in people with diabete...

Non-invasive Characterization of Glycosuria and Identification of Biomarkers in Diabetic Urine Using Fluorescence Spectroscopy and Machine Learning Algorithm.

Journal of fluorescence
The current study presents a steadfast, simple, and efficient approach for the non-invasive determination of glycosuria of diabetes mellitus using fluorescence spectroscopy. A Xenon arc lamp emitting light in the range of 200-950 nm was used as an ex...

Noninvasive blood glucose sensing by secondary speckle pattern artificial intelligence analyses.

Journal of biomedical optics
SIGNIFICANCE: Diabetes is a prevalent disease worldwide that can cause severe health problems. Accurate blood glucose detection is crucial for diabetes management, and noninvasive methods can be more convenient and less painful than traditional finge...

Elastic Deformation of Optical Coherence Tomography Images of Diabetic Macular Edema for Deep-Learning Models Training: How Far to Go?

IEEE journal of translational engineering in health and medicine
UNLABELLED: - Objective: To explore the clinical validity of elastic deformation of optical coherence tomography (OCT) images for data augmentation in the development of deep-learning model for detection of diabetic macular edema (DME).

Attention-based deep learning framework to recognize diabetes disease from cellular retinal images.

Biochemistry and cell biology = Biochimie et biologie cellulaire
A medical disorder known as diabetic retinopathy (DR) affects people who suffer from diabetes. Many people are visually impaired due to DR. Primary cause of DR in patients is high blood sugar, and it affects blood vessels available in the retinal cel...

Explainable artificial intelligence on life satisfaction, diabetes mellitus and its comorbid condition.

Scientific reports
This study uses artificial intelligence for testing (1) whether the comorbidity of diabetes and its comorbid condition is very strong in the middle-aged or old (hypothesis 1) and (2) whether major determinants of the comorbidity are similar for diffe...