AI Medical Compendium Topic

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Diabetes Mellitus

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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.

Efficacy of deep learning-based artificial intelligence models in screening and referring patients with diabetic retinopathy and glaucoma.

Indian journal of ophthalmology
PURPOSE: To analyze the efficacy of a deep learning (DL)-based artificial intelligence (AI)-based algorithm in detecting the presence of diabetic retinopathy (DR) and glaucoma suspect as compared to the diagnosis by specialists secondarily to explore...

Risk assessment of diabetic retinopathy with machine and deep learning models with PPG signals and PWV.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Retinopathy is one of the most common micro vascular impairments in diabetic subjects. Elevated blood glucose leads to capillary occlusion, provoking the uncontrolled increase in local growth of new vessels in the retina. When left untreated, it can ...