Diabetes

Data Homogeneity Effect in Deep Learning-Based Prediction of Type 1 Diabetic Retinopathy.

This study is aimed at evaluating a deep transfer learning-based model for identifying diabetic retinopathy (DR) that was trained using a dataset with high variability and predominant type 2 diabetes (T2D) and comparing model performance with that in patients with type 1 diabetes (T1D). The Kaggle dataset, which is a publicly available dataset, was divided into training and testing Kaggle datasets...

Risk Assessment and Determination of Factors That Cause the Development of Hyperinsulinemia in School-Age Adolescents.

: Hyperinsulinemia and insulin resistance are not synonymous; if the risk of developing insulin resistance in adolescents is monitored, they do not necessarily have hyperinsulinemia. It is considered a condition of pre-diabetes and represents a condition of increased risk of developing DM (diabetes mellitus); it can exist for many years without people having the appropriate symptoms. This study ai...

Multi-step ahead predictive model for blood glucose concentrations of type-1 diabetic patients.

Continuous monitoring of blood glucose (BG) levels is a key aspect of diabetes management. Patients with Type-1 diabetes (T1D) require an effective to...

Machine Learning Methods of Regression for Plasmonic Nanoantenna Glucose Sensing.

The measurement and quantification of glucose concentrations is a field of major interest, whether motivated by potential clinical applications or as ...

The COVID-19 epidemic analysis and diagnosis using deep learning: A systematic literature review and future directions.

Since December 2019, the COVID-19 outbreak has resulted in countless deaths and has harmed all facets of human existence. COVID-19 has been designated...

Elevated Levels of Urinary Biomarkers TIMP-2 and IGFBP-7 Predict Acute Kidney Injury in Neonates after Congenital Heart Surgery.

 This article investigated the utility of urine biomarkers tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor binding pr...

Native BK virus nephropathy in lung transplant: a case report and literature review.

Classically described in renal allografts, BK virus nephropathy is increasingly recognized in native kidneys of other non-renal solid organ transplant...

Explainable Biomarkers for Automated Glomerular and Patient-Level Disease Classification.

Pathologists use multiple microscopy modalities to assess renal biopsy specimens. Besides usual diagnostic features, some changes are too subtle to be...

A stratified analysis of a deep learning algorithm in the diagnosis of diabetic retinopathy in a real-world study.

BACKGROUND: The aim of our research was to prospectively explore the clinical value of a deep learning algorithm (DLA) to detect referable diabetic re...

A Comparative Performance Assessment of Optimized Multilevel Ensemble Learning Model with Existing Classifier Models.

To predict the class level of any classification problem, predictive models are used and mostly a single predictive model is built to predict the clas...

An early model to predict the risk of gestational diabetes mellitus in the absence of blood examination indexes: application in primary health care centres.

BACKGROUND: Gestational diabetes mellitus (GDM) is one of the critical causes of adverse perinatal outcomes. A reliable estimate of GDM in early pregn...

Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions.

Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase ...

Systems biology and machine learning approaches identify drug targets in diabetic nephropathy.

Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the ...

Corticosteroids and mycophenolic acid analogues in immunoglobulin A nephropathy with progressive decline in kidney function.

BACKGROUND: A randomized controlled trial demonstrated a beneficial effect of corticosteroids (CS) + cyclophosphamide followed by azathioprine in prog...

A weakly supervised model for the automated detection of adverse events using clinical notes.

With clinical trials unable to detect all potential adverse reactions to drugs and medical devices prior to their release into the market, accurate po...

Effects of black cumin seed oil on oxidative stress and expression of membrane-cytoskeleton linker proteins, radixin, and moesin in streptozotocin-induced diabetic rat liver.

BACKGROUND AND AIM: This study examined the effects of black cumin seed oil treatment on oxidative stress and the expression of radixin and moesin in ...

A deep learning model for identifying diabetic retinopathy using optical coherence tomography angiography.

As the prevalence of diabetes increases, millions of people need to be screened for diabetic retinopathy (DR). Remarkable advances in technology have ...

Phytogenic compounds from avocado ( L.) extracts; antioxidant activity, amylase inhibitory activity, therapeutic potential of type 2 diabetes.

Diabetes is a worldwide public health disease. Currently, the most effective way to treat diabetes is to mitigate postprandial hyperglycemia by inhibi...

90% Accuracy for Photoplethysmography-Based Non-Invasive Blood Glucose Prediction by Deep Learning with Cohort Arrangement and Quarterly Measured HbA1c.

Previously published photoplethysmography-(PPG) based non-invasive blood glucose (NIBG) measurements have not yet been validated over 500 subjects. As...

Machine Learning-Based Gynecologic Tumor Diagnosis and Its Postoperative Incisional Infection Influence Factor Analysis.

Various factors influencing postoperative incisional infection in gynecologic tumors were analyzed, and the value of quality nursing intervention was ...