AIMC Topic: Biosensing Techniques

Clear Filters Showing 501 to 510 of 517 articles

Machine learning-assisted washing-free detection of extracellular vesicles by target recycling amplification based fluorescent aptasensor for accurate diagnosis of gastric cancer.

Talanta
Extracellular vesicles (EVs) are promising non-invasive biomarkers for cancer diagnosis. EVs proteins play a critical role in tumor progress and metastasis. However, accurately and reliably diagnosing cancers is greatly limited by single protein mark...

Point-of-Care Testing: The Convergence of Innovation and Accessibility in Diagnostics.

Analytical chemistry
Over the years, the evolution of point-of-care testing (POCT) has been driven by technological advancements in materials, design, and artificial intelligence, as well as breakthrough developments in wearable technologies. These innovations are shifti...

Noninvasive blood glucose monitoring using a dual band microwave sensor with machine learning.

Scientific reports
The potential for continuous non-invasive blood glucose monitoring has attracted a lot of interest in the field of medical diagnostics. This paper provides a new shape of a dual-band bandpass filter (DBBPF) acting as a microwave transmission line sen...

A Systematic Review of Sensor-Based Methods for Measurement of Eating Behavior.

Sensors (Basel, Switzerland)
The dynamic process of eating-including chewing, biting, swallowing, food items, eating time and rate, mass, environment, and other metrics-may characterize behavioral aspects of eating. This article presents a systematic review of the use of sensor ...

Label-Free Classification of L-Histidine Vs Artificial Human Sweat Using Laser Scribed Electrodes and a Multi-Layer Perceptron Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A challenge in wearable technology lies in the realtime monitoring of molecular biomarkers associated with human health. Electrochemical sensors are one of the most useful tools for this purpose and are commonly used in health monitoring devices. Ele...

Applications of artificial intelligence and machine learning in dynamic pathway engineering.

Biochemical Society transactions
Dynamic pathway engineering aims to build metabolic production systems embedded with intracellular control mechanisms for improved performance. These control systems enable host cells to self-regulate the temporal activity of a production pathway in ...

Barcodes, co-cultures, and deep learning take genetically encoded biosensor multiplexing to the nth degree.

Molecular cell
Yang et al. (2021) describe a co-culture multiplexed imaging method that can provide an order of magnitude increase in the number of barcoded biosensors that can be imaged in a single experiment.

Cell-Free Biosensors and AI Integration.

Methods in molecular biology (Clifton, N.J.)
Cell-free biosensors hold a great potential as alternatives for traditional analytical chemistry methods providing low-cost low-resource measurement of specific chemicals. However, their large-scale use is limited by the complexity of their developme...

Identification of spectral signature for in situ real-time monitoring of smoltification.

Applied optics
We describe the use of an optical hyperspectral sensing technique to identify the smoltification status of Atlantic salmon (Salmo salar) based on spectral signatures, thus potentially providing smolt producers with an additional tool to verify the os...

Bio-inspired gas sensing: boosting performance with sensor optimization guided by "machine learning".

Faraday discussions
The performance of existing gas sensors often degrades in field conditions because of the loss of measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved sensor selectivity. We are developing a n...