Endocrinology

Diabetes

Latest AI and machine learning research in diabetes for healthcare professionals.

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Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview.

Social determining factors such as the adverse influence of globalization, supermarket growth, fast ...

May 2020 32403349
Intelligent Machine Learning Approach for Effective Recognition of Diabetes in E-Healthcare Using Clinical Data.

Significant attention has been paid to the accurate detection of diabetes. It is a big challenge for...

May 2020 32384737
Variability in Plus Disease Identified Using a Deep Learning-Based Retinopathy of Prematurity Severity Scale.

PURPOSE: Retinopathy of prematurity is a leading cause of childhood blindness worldwide, but clinica...

May 2020 32380115
DR|GRADUATE: Uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images.

Diabetic retinopathy (DR) grading is crucial in determining the adequate treatment and follow up of ...

Apr 2020 32434128
Predicting the Risk of Inpatient Hypoglycemia With Machine Learning Using Electronic Health Records.

OBJECTIVE: We analyzed data from inpatients with diabetes admitted to a large university hospital to...

Apr 2020 32350021
Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study.

BACKGROUND: Deep learning is a novel machine learning technique that has been shown to be as effecti...

Apr 2020 33328056
Artificial Intelligence: The Future for Diabetes Care.

Artificial intelligence (AI) is a fast-growing field and its applications to diabetes, a global pand...

Apr 2020 32325045
Artificial Intelligence and Digital Tools: Future of Diabetes Care.

Diabetes mellitus has become a global threat, especially in the emerging economies. In the United St...

Apr 2020 32586478
Application of deep learning image assessment software VeriSeeā„¢ for diabetic retinopathy screening.

PURPOSE: To develop a deep learning image assessment software VeriSeeā„¢ and to validate its accuracy ...

Apr 2020 32307321
Microaneurysms detection in color fundus images using machine learning based on directional local contrast.

BACKGROUND: As one of the major complications of diabetes, diabetic retinopathy (DR) is a leading ca...

Apr 2020 32295576
Ensemble Deep Learning for Diabetic Retinopathy Detection Using Optical Coherence Tomography Angiography.

PURPOSE: To evaluate the role of ensemble learning techniques with deep learning in classifying diab...

Apr 2020 32818081
Towards implementation of AI in New Zealand national diabetic screening program: Cloud-based, robust, and bespoke.

Convolutional Neural Networks (CNNs) have become a prominent method of AI implementation in medical ...

Apr 2020 32275656
Efficacy for Differentiating Nonglaucomatous Versus Glaucomatous Optic Neuropathy Using Deep Learning Systems.

PURPOSE: We sought to assess the performance of deep learning approaches for differentiating nonglau...

Apr 2020 32247778
Limits of trust in medical AI.

Artificial intelligence (AI) is expected to revolutionise the practice of medicine. Recent advanceme...

Mar 2020 32220870
Deep Learning Classification for Diabetic Foot Thermograms.

According to the World Health Organization (WHO), Diabetes Mellitus (DM) is one of the most prevalen...

Mar 2020 32235780
Modeling the Research Landscapes of Artificial Intelligence Applications in Diabetes (GAP).

The rising prevalence and global burden of diabetes fortify the need for more comprehensive and effe...

Mar 2020 32192211
Diabetic retinopathy and ultrawide field imaging.

The introduction of ultrawide field imaging has allowed the visualization of approximately 82% of th...

Mar 2020 32167854
Lessons Learned About Autonomous AI: Finding a Safe, Efficacious, and Ethical Path Through the Development Process.

Artificial intelligence (AI) describes systems capable of making decisions of high cognitive complex...

Mar 2020 32171769
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