AIMC Topic: Glucose

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Association of urinary metal elements with sarcopenia and glucose metabolism abnormalities: Insights from NHANES data using machine learning approaches.

Ecotoxicology and environmental safety
BACKGROUND: Sarcopenia, a condition marked by the decline of skeletal muscle mass and function, is prevalent in the elderly and closely linked to abnormal glucose metabolism, particularly type 2 diabetes. Hyperglycemia can increase the formation of a...

A Genetic Algorithms-Based Neural Network Model to Monitor Gibberellic Acid GA3 Fermentation Process by Fusarium fujikuroi.

Biotechnology and bioengineering
A genetic algorithm-optimized neural network (ANN-GA) was developed for real-time monitoring of gibberellin (GA3) production during Fusarium fujikuroi fermentation. This model addresses the limitations of traditional off-line detection methods, such ...

Transfer learning and data augmentation for glucose concentration prediction from colorimetric biosensor images.

Mikrochimica acta
A deep learning algorithm is introduced to accurately predict glucose concentrations using colorimetric paper sensor (CPS) images. We used an image dataset from CPS treated with five different glucose concentrations as input for deep learning models....

Machine Learning-Assisted Portable Dual-Readout Biosensor for Visual Detection of Milk Allergen.

Nano letters
Beta-lactoglobulin (β-LG), the primary allergen in cow's milk, makes developing a rapid, sensitive, and convenient detection method essential for individuals with allergies. In this study, a graphdiyne-based self-powered electrochemical biosensor has...

Dynamic glucose enhanced imaging using direct water saturation.

Magnetic resonance in medicine
PURPOSE: Dynamic glucose enhanced (DGE) MRI studies employ CEST or spin lock (CESL) to study glucose uptake. Currently, these methods are hampered by low effect size and sensitivity to motion. To overcome this, we propose to utilize exchange-based li...

Terahertz molecular vibrational sensing using 3D printed anapole meta-biosensor.

Biosensors & bioelectronics
Terahertz (THz) fingerprint sensing utilizes the absorption of fingerprints generated by the unique vibrational characteristics of molecules to achieve substance-specific identification. By taking full advance of the anapole mode induced-biosensor co...

Machine Learning-Driven D-Glucose Prediction Using a Novel Biosensor for Non-Invasive Diabetes Management.

Biosensors
Developing reliable noninvasive diagnostic and monitoring systems for diabetes remains a significant challenge, especially in the e-healthcare domain, due to computational inefficiencies and limited predictive accuracy in current approaches. The curr...

Harnessing near-infrared and Raman spectral sensing and artificial intelligence for real-time monitoring and precision control of bioprocess.

Bioresource technology
Effective monitoring and control of bioprocesses are critical for industrial biomanufacturing. This study demonstrates the integration of near-infrared and Raman spectroscopy for real-time monitoring and precise control of gentamicin fermentation. Th...

mCNN-glucose: Identifying families of glucose transporters using a deep convolutional neural network based on multiple-scanning windows.

International journal of biological macromolecules
Glucose transporters are essential carrier proteins that function on the phospholipid bilayer to facilitate glucose diffusion across cell membranes. The transporters play many physiological and pathological roles in addition to absorption and metabol...

Artificial Intelligence in Diagnostics: Enhancing Urine Test Accuracy Using a Mobile Phone-Based Reading System.

Annals of laboratory medicine
BACKGROUND: Urinalysis, an essential diagnostic tool, faces challenges in terms of standardization and accuracy. The use of artificial intelligence (AI) with mobile technology can potentially solve these challenges. Therefore, we investigated the eff...