AI Medical Compendium Topic

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Glucose

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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...

A stretchable, adhesive, and wearable hydrogel-based patches based on a bilayer PVA composite for online monitoring of sweat by artificial intelligence-assisted smartphones.

Talanta
Real-time monitoring of sweat using wearable devices faces challenges such as limited adhesion, mechanical flexibility, and accurate detection. In this work, we present a stretchable, adhesive, bilayer hydrogel-based patch designed for continuous mon...

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...

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...

MIP-based electrochemical sensor with machine learning for accurate ZIKV detection in protein- and glucose-rich urine.

Analytical biochemistry
Nowadays, a multitude of biosensors are being developed worldwide. However, a significant challenge arises when these biosensors are tested in real sample environments, as many of them fail to perform as expected. This can lead to ambiguous results a...

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...

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...

Integrating Bioinformatics and Machine Learning to Identify Glucose Metabolism-Related Biomarkers with Diagnostic and Prognostic Value for Patients with Kidney Renal Clear Cell Carcinoma.

Archivos espanoles de urologia
BACKGROUND: Glucose metabolism plays a critical role in the development and progression of kidney renal clear cell carcinoma (KIRC). This study aimed to identify glucose metabolism-related biomarkers (GRBs) and therapeutic targets for KIRC diagnosis ...

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....

Optoelectronic-Coupled-Driven Microrobot for Biological Cargo Transport in Conductive Isosmotic Glucose Solution.

ACS applied materials & interfaces
Electric field-driven micro/nanorobots, as micro/nanodevices with autonomous motion capability, have emerged as promising candidates for targeted cargo delivery in biomedical applications due to their advantages of label-free operation, selectivity, ...