AIMC Topic: Colorimetry

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Machine reading and recovery of colors for hemoglobin-related bioassays and bioimaging.

Science advances
Despite advances in machine learning and computer vision for biomedical imaging, machine reading and learning of colors remain underexplored. Color consistency in computer vision, color constancy in human perception, and color accuracy in biomedical ...

Monitoring Amphetamine and Methamphetamine Mixtures Based on Deep Learning Involves Colorimetric Sensing.

Analytical chemistry
Precise recognition and discrimination of highly similar analytes (either in structure or property) with distinguishable sensing responses are challenging but significant in the practical application of drug seizing, food additive inspection, environ...

A data fusion system based on attenuated total reflectance mid-infrared spectroscopy and colorimetry combined with chemometrics for monitoring the fermentation process of Candida utilis.

Talanta
The fermentation of Candida utilis has become a cost-effective and high-yield process, characterized by its high nutritional value, high productivity, and short fermentation time. To efficiently and comprehensively monitor the fermentation process of...

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...

Robotic-based Experimental Procedure for Colorimetric Gas Sensing Development.

Journal of visualized experiments : JoVE
This paper presents a robot-based experimental program aimed at developing an efficient and fast colorimetric gas sensor. The program employs an automated Design-Build-Test-learning (DBTL) approach, which optimizes the search process iteratively whil...

TimePAD─Unveiling Temporal Sequence ELISA Signal by Deep Learning for Rapid Readout and Improved Accuracy in a Microfluidic Paper-Based Analytical Platform.

Analytical chemistry
The integration of paper-based microfluidics with deep learning represents a pivotal trend in enhancing diagnostic capabilities. This paper introduces a new approach to improve the performance of a paper-based microfluidic enzyme-linked immunosorbent...

Dual-Mode Colorimetric/SERS Lateral Flow Immunoassay with Machine Learning-Driven Optimization for Ultrasensitive Mycotoxin Detection.

Analytical chemistry
Detecting and quantifying mycotoxins using LFIA are challenging due to the need for high sensitivity and accuracy. To address this, a dual-mode colorimetric-SERS LFIA was developed for detecting deoxynivalenol (DON). Rhodium nanocores provided strong...

Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles.

Frontiers in immunology
Lung cancer is a devastating public health threat and a leading cause of cancer-related deaths. Therefore, it is imperative to develop sophisticated techniques for the non-invasive detection of lung cancer. Extracellular vesicles expressing programme...

Machine learning assisted multi-signal nanozyme sensor array for the antioxidant phenolic compounds intelligent recognition.

Food chemistry
Identifying antioxidant phenolic compounds (APs) in food plays a crucial role in understanding their biological functions and associated health benefits. Here, a bifunctional Cu-1,3,5-benzenetricarboxylic acid (Cu-BTC) nanozyme was successfully prepa...