Diabetes

Case of slowly progressive type 1 diabetes mellitus with drastically reduced insulin secretory capacity after immune checkpoint inhibitor treatment for advanced renal cell carcinoma.

We encountered a 55-year-old Japanese man with advanced renal cell carcinoma and slowly progressive ...

Humanoid robot-assisted interventions among children with diabetes: A systematic scoping review.

BACKGROUND: Although the humanoid robot is highly engaging for children, whether humanoid robot-assi...

Machine Learning Models to Predict Childhood and Adolescent Obesity: A Review.

The prevalence of childhood and adolescence overweight an obesity is raising at an alarming rate in ...

Diagnosis of diabetes in pregnant woman using a Chaotic-Jaya hybridized extreme learning machine model.

As stated by World Health Organization (WHO) report, 246 million individuals have suffered with diab...

A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism.

BACKGROUND: Semisupervised and unsupervised anomaly detection methods have been widely used in vario...

Artificial intelligence and deep learning in glaucoma: Current state and future prospects.

Over the past few years, there has been an unprecedented and tremendous excitement for artificial in...

Statistical inference for natural language processing algorithms with a demonstration using type 2 diabetes prediction from electronic health record notes.

The pointwise mutual information statistic (PMI), which measures how often two words occur together ...

Discovery of different metabotypes in overconditioned dairy cows by means of machine learning.

Using data from targeted metabolomics in serum in combination with machine learning (ML) approaches,...

Economic Challenges of Artificial Intelligence Adoption for Diabetic Retinopathy.

Research of Epidemic Big Data Based on Improved Deep Convolutional Neural Network.

In recent years, with the acceleration of the aging process and the aggravation of life pressure, th...

Early detection of type 2 diabetes mellitus using machine learning-based prediction models.

Most screening tests for T2DM in use today were developed using multivariate regression methods that...

EAGA-MLP-An Enhanced and Adaptive Hybrid Classification Model for Diabetes Diagnosis.

Disease diagnosis is a critical task which needs to be done with extreme precision. In recent times,...

Leveraging Multimodal Deep Learning Architecture with Retina Lesion Information to Detect Diabetic Retinopathy.

PURPOSE: To improve disease severity classification from fundus images using a hybrid architecture w...

Deep Physiological Model for Blood Glucose Prediction in T1DM Patients.

Accurate estimations for the near future levels of blood glucose are crucial for Type 1 Diabetes Mel...

A deep learning approach based on convolutional LSTM for detecting diabetes.

Diabetes is a chronic disease that occurs when the pancreas does not generate sufficient insulin or ...

Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors.

Wearable continuous glucose monitoring (CGM) sensors are revolutionizing the treatment of type 1 dia...

Identification of glomerular lesions and intrinsic glomerular cell types in kidney diseases via deep learning.

Identification of glomerular lesions and structures is a key point for pathological diagnosis, treat...

Fatal case of hospital-acquired hypernatraemia in a neonate: lessons learned from a tragic error.

A 3-week-old boy with viral gastroenteritis was by error given 200 mL 1 mmol/mL hypertonic saline in...

Comparison of smartphone-based retinal imaging systems for diabetic retinopathy detection using deep learning.

BACKGROUND: Diabetic retinopathy (DR), the most common cause of vision loss, is caused by damage to ...

Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients.

BACKGROUND/AIMS: Human grading of digital images from diabetic retinopathy (DR) screening programmes...

Near-optimal insulin treatment for diabetes patients: A machine learning approach.

Blood glycemic control is crucial for minimizing severe side effects in diabetes mellitus. Currently...