AIMC Topic: Diabetes Mellitus, Type 2
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Physical performance strongly predicts all-cause mortality risk in a real-world population of older diabetic patients: machine learning approach for mortality risk stratification.
Frontiers in endocrinology
Apr 30, 2024
BACKGROUND: Prognostic risk stratification in older adults with type 2 diabetes (T2D) is important for guiding decisions concerning advance care planning.
Autonomous artificial intelligence versus teleophthalmology for diabetic retinopathy.
European journal of ophthalmology
Apr 24, 2024
To assess the role of artificial intelligence (AI) based automated software for detection of Diabetic Retinopathy (DR) compared with the evaluation of digital retinography by two double masked retina specialists. Two-hundred one patients (mean age ...
Physical Activity Detection for Diabetes Mellitus Patients Using Recurrent Neural Networks.
Sensors (Basel, Switzerland)
Apr 10, 2024
Diabetes mellitus (DM) is a persistent metabolic disorder associated with the hormone insulin. The two main types of DM are type 1 (T1DM) and type 2 (T2DM). Physical activity plays a crucial role in the therapy of diabetes, benefiting both types of p...
Application of machine learning in affordable and accessible insulin management for type 1 and 2 diabetes: A comprehensive review.
Artificial intelligence in medicine
Apr 4, 2024
Proper insulin management is vital for maintaining stable blood sugar levels and preventing complications associated with diabetes. However, the soaring costs of insulin present significant challenges to ensuring affordable management. This paper con...
Population-Specific Glucose Prediction in Diabetes Care With Transformer-Based Deep Learning on the Edge.
IEEE transactions on biomedical circuits and systems
Apr 1, 2024
Leveraging continuous glucose monitoring (CGM) systems, real-time blood glucose (BG) forecasting is essential for proactive interventions, playing a crucial role in enhancing the management of type 1 diabetes (T1D) and type 2 diabetes (T2D). However,...
A Siamese ResNeXt network for predicting carotid intimal thickness of patients with T2DM from fundus images.
Frontiers in endocrinology
Mar 14, 2024
OBJECTIVE: To develop and validate an artificial intelligence diagnostic model based on fundus images for predicting Carotid Intima-Media Thickness (CIMT) in individuals with Type 2 Diabetes Mellitus (T2DM).
A novel interpretable deep transfer learning combining diverse learnable parameters for improved T2D prediction based on single-cell gene regulatory networks.
Scientific reports
Feb 24, 2024
Accurate deep learning (DL) models to predict type 2 diabetes (T2D) are concerned not only with targeting the discrimination task but also with learning useful feature representation. However, existing DL tools are far from perfect and do not provide...
Improved Glycemic Control through Robot-Assisted Remote Interview for Outpatients with Type 2 Diabetes: A Pilot Study.
Medicina (Kaunas, Lithuania)
Feb 15, 2024
: Our research group developed a robot-assisted diabetes self-management monitoring system to support Certified Diabetes Care and Education Specialists (CDCESs) in tracking the health status of patients with type 2 diabetes (T2D). This study aimed to...
Efficacy and safety of insulin glargine 300 units/mL vs insulin degludec in patients with type 1 and type 2 diabetes: a systematic review and meta-analysis.
Frontiers in endocrinology
Jan 19, 2024
BACKGROUND: Ultra-long-acting insulin analogs [insulin degludec (IDeg) and insulin glargine 300 units/mL (IGla-300)] offer a longer duration of action with less risk of hypoglycemia compared to other long-acting insulins. However, data about the comp...
Association between neutrophil-to-lymphocyte ratio and diabetic kidney disease in type 2 diabetes mellitus patients: a cross-sectional study.
Frontiers in endocrinology
Jan 4, 2024
AIMS: This investigation examined the possibility of a relationship between neutrophil-to-lymphocyte ratio (NLR) and diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients.
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