AIMC Topic: Diabetes Mellitus
Clear Filters Showing 141 to 150 of 441 articles
Automatic interpretation and clinical evaluation for fundus fluorescein angiography images of diabetic retinopathy patients by deep learning.
The British journal of ophthalmology
Nov 22, 2023
BACKGROUND/AIMS: Fundus fluorescein angiography (FFA) is an important technique to evaluate diabetic retinopathy (DR) and other retinal diseases. The interpretation of FFA images is complex and time-consuming, and the ability of diagnosis is uneven a...
A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring.
Nature biomedical engineering
Nov 6, 2023
The complex relationships between continuously monitored health signals and therapeutic regimens can be modelled via machine learning. However, the clinical implementation of the models will require changes to clinical workflows. Here we outline Clin...
Deep-learning-based natural-language-processing models to identify cardiovascular disease hospitalisations of patients with diabetes from routine visits' text.
Scientific reports
Nov 5, 2023
Writing notes is the most widespread method to report clinical events. Therefore, most of the information about the disease history of a patient remains locked behind free-form text. Natural language processing (NLP) provides a solution to automatica...
Predicting of diabetic retinopathy development stages of fundus images using deep learning based on combined features.
PloS one
Oct 20, 2023
The number of diabetic retinopathy (DR) patients is increasing every year, and this causes a public health problem. Therefore, regular diagnosis of diabetes patients is necessary to avoid the progression of DR stages to advanced stages that lead to b...
Artificial intelligence in diabetes management: Advancements, opportunities, and challenges.
Cell reports. Medicine
Oct 2, 2023
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
Oct 2, 2023
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
Sep 21, 2023
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
Aug 30, 2023
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
Aug 7, 2023
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
Aug 3, 2023
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...
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