Diabetes

A data-driven approach to referable diabetic retinopathy detection.

UNLABELLED: Prior art on automated screening of diabetic retinopathy and direct referral decision shows promising performance; yet most methods build upon complex hand-crafted features whose performance often fails to generalize.

A Novel Weakly Supervised Multitask Architecture for Retinal Lesions Segmentation on Fundus Images.

Obtaining the complete segmentation map of retinal lesions is the first step toward an automated diagnosis tool for retinopathy that is interpretable in its decision-making. However, the limited availability of ground truth lesion detection maps at a pixel level restricts the ability of deep segmentation neural networks to generalize over large databases. In this paper, we propose a novel approach...

MetaPheno: A critical evaluation of deep learning and machine learning in metagenome-based disease prediction.

The human microbiome plays a number of critical roles, impacting almost every aspect of human health and well-being. Conditions in the microbiome have...

Risk-based postprandial hypoglycemia forecasting using supervised learning.

BACKGROUND: Predicting insulin-induced postprandial hypoglycemic events is critical for the safety of type 1 diabetes patients because an early warnin...

Detecting Hypoglycemia Incidents Reported in Patients' Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance.

BACKGROUND: Improper dosing of medications such as insulin can cause hypoglycemic episodes, which may lead to severe morbidity or even death. Although...

Light-driven ultrasensitive self-powered cytosensing of circulating tumor cells via integration of biofuel cells and a photoelectrochemical strategy.

Herein, a light-driven, membrane-less and mediator-less self-powered cytosensing platform via integration of biofuel cells (BFCs) and a photoelectroch...

Simultaneous spatiotemporal tracking and oxygen sensing of transient implants in vivo using hot-spot MRI and machine learning.

A varying oxygen environment is known to affect cellular function in disease as well as activity of various therapeutics. For transient structures, wh...

Accuracy of ultrawide-field fundus ophthalmoscopy-assisted deep learning for detecting treatment-naïve proliferative diabetic retinopathy.

PURPOSE: We investigated using ultrawide-field fundus images with a deep convolutional neural network (DCNN), which is a machine learning technology, ...

Using natural language processing and machine learning to classify health literacy from secure messages: The ECLIPPSE study.

Limited health literacy is a barrier to optimal healthcare delivery and outcomes. Current measures requiring patients to self-report limitations are t...

Discovering the Type 2 Diabetes in Electronic Health Records Using the Sparse Balanced Support Vector Machine.

The diagnosis of type 2 diabetes (T2D) at an early stage has a key role for an adequate T2D integrated management system and patient's follow-up. Rece...

Circulating Levels of Soluble Klotho and Fibroblast Growth Factor 23 in Diabetic Patients and Its Association with Early Nephropathy.

INTRODUCTION: Diabetic nephropathy is a leading cause of chronic kidney disease (CKD). In diabetes, changes in serum levels of both soluble alpha Klot...

Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

PURPOSE: Accurate image-based ophthalmic diagnosis relies on fundus image clarity. This has important implications for the quality of ophthalmic diagn...

Identification of Diabetic Patients through Clinical and Para-Clinical Features in Mexico: An Approach Using Deep Neural Networks.

Diabetes is a chronic and noncommunicable but preventable disease that is affecting the Mexican population at worrying levels, being the first place i...

Fluorescent silicon nanoparticles inhibit the amyloid fibrillation of insulin.

Amyloid fibrillation of proteins is likely a key factor leading to the development of amyloidosis-associated diseases. Inhibiting amyloid fibrillation...

Prediction of Hypoglycemia During Aerobic Exercise in Adults With Type 1 Diabetes.

BACKGROUND: Fear of exercise related hypoglycemia is a major reason why people with type 1 diabetes (T1D) do not exercise. There is no validated predi...

Artificial neural networks in the selection of shoe lasts for people with mild diabetes.

This research addressed the selection of shoe lasts for footwear design to help relieve the pain associated with diabetic neuropathy and foot ulcers. ...

Sleep Duration and Diabetic Kidney Disease.

Abnormally short or long durations of sleep have been proposed as a risk factors for diabetes and its micro- and macro-vascular complications. Howeve...

Elevated Serum Growth Differentiation Factor 15 Levels in Hyperthyroid Patients.

Recent studies have shown that growth differentiation factor 15 (GDF15), a member of the transforming growth factor-β (TGF-β)/bone morphogenetic prot...

Machine Learning Models for the Prediction of Chemotherapy-Induced Peripheral Neuropathy.

PURPOSE: Chemotherapy-induced peripheral neuropathy (CIPN) is a common adverse side effect of cancer chemotherapy that can be life debilitating and ca...

Fully automated detection of retinal disorders by image-based deep learning.

PURPOSE: With the aging population and the global diabetes epidemic, the prevalence of age-related macular degeneration (AMD) and diabetic macular ede...