AIMC Topic: Biosensing Techniques

Clear Filters Showing 221 to 230 of 383 articles

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism.

Nature communications
Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be c...

Machine learning-driven electronic identifications of single pathogenic bacteria.

Scientific reports
A rapid method for screening pathogens can revolutionize health care by enabling infection control through medication before symptom. Here we report on label-free single-cell identifications of clinically-important pathogenic bacteria by using a poly...

SERS-based lateral flow assay combined with machine learning for highly sensitive quantitative analysis of Escherichia coli O157:H7.

Analytical and bioanalytical chemistry
In the present study, surface-enhanced Raman scattering-based lateral flow assay (SERS-LFA) strips were applied to promptly and sensitively detect Escherichia coli O157:H7 (E. coli O157:H7) to ensure food safety. The SERS nanotags were prepared by co...

Application of Artificial Neural Networks for Accurate Determination of the Complex Permittivity of Biological Tissue.

Sensors (Basel, Switzerland)
Medical devices making use of radio frequency (RF) and microwave (MW) fields have been studied as alternatives to existing diagnostic and therapeutic modalities since they offer several advantages. However, the lack of accurate knowledge of the compl...

Improved Antibiotic Detection in Raw Milk Using Machine Learning Tools over the Absorption Spectra of a Problem-Specific Nanobiosensor.

Sensors (Basel, Switzerland)
In this article we present the development of a biosensor system that integrates nanotechnology, optomechanics and a spectral detection algorithm for sensitive quantification of antibiotic residues in raw milk of cow. Firstly, nanobiosensors were des...

Using machine learning for real-time BAC estimation from a new-generation transdermal biosensor in the laboratory.

Drug and alcohol dependence
BACKGROUND: Transdermal biosensors offer a noninvasive, low-cost technology for the assessment of alcohol consumption with broad potential applications in addiction science. Older-generation transdermal devices feature bulky designs and sparse sampli...

Analysis of Precision and Stability of Hand Tracking with Leap Motion Sensor.

Sensors (Basel, Switzerland)
In this analysis, we present results from measurements performed to determine the stability of a hand tracking system and the accuracy of the detected palm and finger's position. Measurements were performed for the evaluation of the sensor for an app...

Robotic DNA Nanostructures.

ACS synthetic biology
Over the past decade, DNA nanotechnology has spawned a broad variety of functional nanostructures tailored toward the enabled state at which applications are coming increasingly in view. One of the branches of these applications is in synthetic biolo...

Artificial intelligence biosensors: Challenges and prospects.

Biosensors & bioelectronics
Artificial intelligence (AI) and wearable sensors are two essential fields to realize the goal of tailoring the best precision medicine treatment for individual patients. Integration of these two fields enables better acquisition of patient data and ...

Machine learning-based design of meta-plasmonic biosensors with negative index metamaterials.

Biosensors & bioelectronics
In this work, we explore the performance of plasmonic biosensor designs that integrate metamaterials based on machine learning algorithms. The meta-plasmonic biosensors were designed for optimized detection of DNA with a layer of double negative meta...