AI Medical Compendium Journal:
The Analyst

Showing 1 to 10 of 43 articles

Tyramide signal amplification for a highly sensitive multiplex immunoassay based on encoded hydrogel microparticles.

The Analyst
Proteins play a crucial role as mediators of immune regulation, homeostasis, and metabolism, making their quantification essential for understanding disease mechanisms in biomedical research and clinical diagnostics. However, conventional methods whe...

Optimized machine learning approaches to combine surface-enhanced Raman scattering and infrared data for trace detection of xylazine in illicit opioids.

The Analyst
Infrared absorption spectroscopy and surface-enhanced Raman spectroscopy were integrated into three data fusion strategies-hybrid (concatenated spectra), mid-level (extracted features from both datasets) and high-level (fusion of predictions from bot...

An improved cancer diagnosis algorithm for protein mass spectrometry based on PCA and a one-dimensional neural network combining ResNet and SENet.

The Analyst
Cancer is one of the most serious health problems worldwide. Because cancer has no specific symptoms in its early stages, it is often not diagnosed until it is in advanced stages, reducing the likelihood of successful treatment. Therefore, early diag...

Liquid saliva-based Raman spectroscopy device with on-board machine learning detects COVID-19 infection in real-time.

The Analyst
With greater population density, the likelihood of viral outbreaks achieving pandemic status is increasing. However, current viral screening techniques use specific reagents, and as viruses mutate, test accuracy decreases. Here, we present the first ...

Machine learning powered detection of biological toxins in association with confined lateral flow immunoassay (c-LFA).

The Analyst
Biological weapons, primarily dispersed as aerosols, can spread not only to the targeted area but also to adjacent regions following the movement of air driven by wind. Thus, there is a growing demand for toxin analysis because biological weapons are...

Metabolic profiling of murine radiation-induced lung injury with Raman spectroscopy and comparative machine learning.

The Analyst
Radiation-induced lung injury (RILI) is a dose-limiting toxicity for cancer patients receiving thoracic radiotherapy. As such, it is important to characterize metabolic associations with the early and late stages of RILI, namely pneumonitis and pulmo...

Paper spray mass spectrometry combined with machine learning as a rapid diagnostic for chronic kidney disease.

The Analyst
A new analytical method for chronic kidney disease (CKD) detection utilizing paper spray mass spectrometry (PS-MS) combined with machine learning is presented. The analytical protocol is rapid and simple, based on metabolic profile alterations in uri...

Stratification of tumour cell radiation response and metabolic signatures visualization with Raman spectroscopy and explainable convolutional neural network.

The Analyst
Reprogramming of cellular metabolism is a driving factor of tumour progression and radiation therapy resistance. Identifying biochemical signatures associated with tumour radioresistance may assist with the development of targeted treatment strategie...

Guided principal component analysis (GPCA): a simple method for improving detection of a known analyte.

The Analyst
There is increasing interest in the application of Raman spectroscopy in a medical setting, ranging from supporting real-time clinical decisions surgical margins to assisting pathologists with disease classification. However, there remain a number o...

Dimensionality reduction for deep learning in infrared microscopy: a comparative computational survey.

The Analyst
While infrared microscopy provides molecular information at spatial resolution in a label-free manner, exploiting both spatial and molecular information for classifying the disease status of tissue samples constitutes a major challenge. One strategy ...