AIMC Topic: Diabetes Mellitus

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Noninvasive detection of diabetes in obstructive sleep apnea based on overnight SpO signal and deep learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The prevalence of obstructive sleep apnea comorbid with diabetes is high while the awareness of diabetes is low. There is a strong need for new diagnostic biomarkers to detect diabetes at an early stage. Therefore, we aimed to establish an automatic,...

Predicting Diabetes in Canadian Adults Using Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Rising diabetes rates have led to increased healthcare costs and health complications. An estimated half of diabetes cases remain undiagnosed. Early and accurate diagnosis is crucial to mitigate disease progression and associated risks. This study ad...

StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides.

Bioinformatics (Oxford, England)
MOTIVATION: Diabetes is a chronic metabolic disorder that has been a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation across the world. To alleviate the impact of diabetes, researchers have developed the next...

Federated Diabetes Prediction in Canadian Adults Using Real-world Cross-Province Primary Care Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Integrating Electronic Health Records (EHR) and the application of machine learning present opportunities for enhancing the accuracy and accessibility of data-driven diabetes prediction. In particular, developing data-driven machine learning models c...

Binary fire hawks optimizer with deep learning driven non-invasive diabetes detection and classification.

Bratislavske lekarske listy
Non-invasive diabetes detection refers to the utilization and development of technologies and methods that can monitor and diagnose diabetes without requiring invasive procedures, namely invasive glucose monitoring or blood sampling. The objective is...

Hybrid CNN-LSTM for Predicting Diabetes: A Review.

Current diabetes reviews
BACKGROUND: Diabetes is a common and deadly chronic disease caused by high blood glucose levels that can cause heart problems, neurological damage, and other illnesses. Through the early detection of diabetes, patients can live healthier lives. Many ...

Risk Stratification for Diabetic Retinopathy Screening Order Using Deep Learning: A Multicenter Prospective Study.

Translational vision science & technology
PURPOSE: Real-world evaluation of a deep learning model that prioritizes patients based on risk of progression to moderate or worse (MOD+) diabetic retinopathy (DR).

Changes of plasma Rap1A levels in patients with in-stent restenosis after percutaneous coronary intervention and the underlying mechanisms.

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
OBJECTIVES: Percutaneous coronary intervention (PCI) is one of the most important treatments for coronary artery disease (CAD). However, in-stent restenosis (ISR) after PCI is a serious complication without effective measures for prevention and treat...

Deep learning-based analysis of infrared fundus photography for automated diagnosis of diabetic retinopathy with cataracts.

Journal of cataract and refractive surgery
PURPOSE: To develop deep learning-based networks for the diagnosis of diabetic retinopathy (DR) with cataracts based on infrared fundus images.