AIMC Topic: Diabetes Mellitus
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Integrative analysis of potential diagnostic markers and therapeutic targets for glomerulus-associated diabetic nephropathy based on cellular senescence.
Frontiers in immunology
Jan 8, 2024
INTRODUCTION: Diabetic nephropathy (DN), distinguished by detrimental changes in the renal glomeruli, is regarded as the leading cause of death from end-stage renal disease among diabetics. Cellular senescence plays a paramount role, profoundly affec...
A deep learning system for predicting time to progression of diabetic retinopathy.
Nature medicine
Jan 4, 2024
Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and va...
Artificial intelligence model for early detection of diabetes.
Biomedica : revista del Instituto Nacional de Salud
Dec 29, 2023
Introduction. Diabetes is a chronic disease characterized by a high blood glucose level. It can lead to complications that affect the quality of life and increase the costs of healthcare. In recent years, prevalence and mortality rates have increased...
Deep learning innovations in diagnosing diabetic retinopathy: The potential of transfer learning and the DiaCNN model.
Computers in biology and medicine
Dec 11, 2023
Diabetic retinopathy (DR) is a significant cause of vision impairment, emphasizing the critical need for early detection and timely intervention to avert visual deterioration. Diagnosing DR is inherently complex, as it necessitates the meticulous exa...
A novel multi-feature learning model for disease diagnosis using face skin images.
Computers in biology and medicine
Dec 10, 2023
BACKGROUND: Facial skin characteristics can provide valuable information about a patient's underlying health conditions.
Exhaled breath signal analysis for diabetes detection: an optimized deep learning approach.
Computer methods in biomechanics and biomedical engineering
Dec 7, 2023
In this study, a flexible deep learning system for breath analysis is created using an optimal hybrid deep learning model. To improve the quality of the gathered breath signals, the raw data are first pre-processed. Then, the most relevant features l...
Machine Learning and Deep Learning Techniques Applied to Diabetes Research: A Bibliometric Analysis.
Journal of diabetes science and technology
Dec 4, 2023
BACKGROUND: The use of machine learning and deep learning techniques in the research on diabetes has garnered attention in recent times. Nonetheless, few studies offer a thorough picture of the knowledge generation landscape in this field. To address...
A novel approach for diabetic foot diagnosis: Deep learning-based detection of lower extremity arterial stenosis.
Diabetes research and clinical practice
Dec 2, 2023
PURPOSE OF THE STUDY: Assessing the lower extremity arterial stenosis scores (LEASS) in patients with diabetic foot ulcer (DFU) is a challenging task that requires considerable time and efforts from physicians, and it may yield varying results. The p...
A Smart Sensing Technologies-Based Intelligent Healthcare System for Diabetes Patients.
Sensors (Basel, Switzerland)
Dec 1, 2023
An Artificial Intelligence (AI)-enabled human-centered smart healthcare monitoring system can be useful in life saving, specifically for diabetes patients. Diabetes and heart patients need real-time and remote monitoring and recommendation-based medi...
Automated segmentation of ultra-widefield fluorescein angiography of diabetic retinopathy using deep learning.
The British journal of ophthalmology
Nov 22, 2023
BACKGROUND/AIMS: Retinal capillary non-perfusion (NP) and neovascularisation (NV) are two of the most important angiographic changes in diabetic retinopathy (DR). This study investigated the feasibility of using deep learning (DL) models to automatic...
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