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Glucose

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Selecting the best machine learning algorithm to support the diagnosis of Non-Alcoholic Fatty Liver Disease: A meta learner study.

PloS one
BACKGROUND & AIMS: Liver ultrasound scan (US) use in diagnosing Non-Alcoholic Fatty Liver Disease (NAFLD) causes costs and waiting lists overloads. We aimed to compare various Machine learning algorithms with a Meta learner approach to find the best ...

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast during ramadan (The PROFAST - IT Ramadan study).

Diabetes research and clinical practice
OBJECTIVE: To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapi...

Developing an Individual Glucose Prediction Model Using Recurrent Neural Network.

Sensors (Basel, Switzerland)
In this study, we propose a personalized glucose prediction model using deep learning for hospitalized patients who experience Type-2 diabetes. We aim for our model to assist the medical personnel who check the blood glucose and control the amount of...

Recent Advancements and Future Prospects on E-Nose Sensors Technology and Machine Learning Approaches for Non-Invasive Diabetes Diagnosis: A Review.

IEEE reviews in biomedical engineering
Diabetes mellitus, commonly measured through an invasive process which although is accurate, has manifold drawbacks especially when multiple reading are required at regular intervals. Accordingly, there is a need to develop a dependable non-invasive ...

GT-Finder: Classify the family of glucose transporters with pre-trained BERT language models.

Computers in biology and medicine
Recently, language representation models have drawn a lot of attention in the field of natural language processing (NLP) due to their remarkable results. Among them, BERT (Bidirectional Encoder Representations from Transformers) has proven to be a si...

Polypyrrole-Based Nanorobots Powered by Light and Glucose for Pollutant Degradation in Water.

ACS applied materials & interfaces
Novel photoactive and enzymatically active nanomotors were developed for efficient organic pollutant degradation. The developed preparation route is simple and scalable. Light-absorbing polypyrrole nanoparticles were equipped with a bi-enzyme [glucos...

Screening of a novel free fatty acid receptor 1 (FFAR1) agonist peptide by phage display and machine learning based-amino acid substitution.

Biochemical and biophysical research communications
Free fatty acid receptor 1 (FFAR1 or GPR40) has attracted attention for the treatment of type 2 diabetes mellitus, and various small-molecule agonists have been developed. However, most FFAR1 agonists as well as endogenous ligands, such as linoleic a...

An Artificial-Intelligence-Discovered Functional Ingredient, NRT_N0G5IJ, Derived from , Decreases HbA1c in a Prediabetic Population.

Nutrients
The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for individuals to develop type 2 diabetes and associated diseases. Therefore, it is necessary to develop nutritional strategies to maintain healthy glucose l...

A Zwitterionic-Aromatic Motif-Based ionic skin for highly biocompatible and Glucose-Responsive sensor.

Journal of colloid and interface science
Electronic skins that can sense external stimuli have been of great significance in artificial intelligence and smart wearable devices in recent years. However, most of current skin materials are unable to achieve high biocompatibility and anti-bacte...