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Combination of headspace single-drop microextraction (HS-SDME) with a nickel-embedded paper-based analytical device for cyanide quantification.

Analytica chimica acta
BACKGROUND: Cyanide anion can be found in foodstuffs, tobacco smoke and a variety of types of waters, mainly originating from anthropogenic activities. Due to its highly toxic nature, several agencies have established limits for cyanide levels in wat...

Paper-based fluorescence sensor array with functionalized carbon quantum dots for bacterial discrimination using a machine learning algorithm.

Analytical and bioanalytical chemistry
The rapid discrimination of bacteria is currently an emerging trend in the fields of food safety, medical detection, and environmental observation. Traditional methods often require lengthy culturing processes, specialized analytical equipment, and b...

A Paper-Based Multiplexed Serological Test to Monitor Immunity against SARS-COV-2 Using Machine Learning.

ACS nano
The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the disease. Given the sustained high infectivity and evolution of SARS-CoV-2, there is an ongoing interest...

Deep Learning-Based Kinetic Analysis in Paper-Based Analytical Cartridges Integrated with Field-Effect Transistors.

ACS nano
This study explores the fusion of a field-effect transistor (FET), a paper-based analytical cartridge, and the computational power of deep learning (DL) for quantitative biosensing via kinetic analyses. The FET sensors address the low sensitivity cha...

An artificial intelligence handheld sensor for direct reading of nickel ion and ethylenediaminetetraacetic acid in food samples using ratiometric fluorescence cellulose paper microfluidic chip.

International journal of biological macromolecules
User-friendly in-field sensing protocol is crucial for the effective tracing of intended analytes under less-developed countries or resources-limited environments. Nevertheless, existing sensing strategies require professional technicians and expensi...

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...

Machine learning assisted paper-based fluorescent sensor array with metal-doped multicolor carbon quantum dots for identification and inactivation of bacteria.

Talanta
Bacterial infection is a thorny threat in a variety of fields, including medicine, environment, food, and agriculture. A multifunctional platform that meets the demands of both bacterial identification and real-time inactivation is urgently needed. T...

ZnO nanoflower-mediated paper-based electrochemical biosensor for perfect classification of cardiac biomarkers with physics-informed machine learning.

Mikrochimica acta
The widespread exposure of acute myocardial infarction globally demands an ultrasensitive, rapid, and cost-effective biosensor for troponin-I and T in a dynamic concentration range. Traditionally, the saturation of sensor response limits accurate pre...

AI-Assisted Label-Free Monitoring Bone Mineral Metabolism on Demineralized Bone Paper.

ACS biomaterials science & engineering
Effective drug development for bone-related diseases, such as osteoporosis and metastasis, is hindered by the lack of physiologically relevant in vitro models. Traditional platforms, including standard tissue culture plastic, fail to replicate the st...

ML-UrineQuant: A machine learning program for identifying and quantifying mouse urine on absorbent paper.

Physiological reports
The void spot assay has gained popularity as a way of assessing functional bladder voiding parameters in mice, but analyzing the size and distribution of urine spot patterns on filter paper with software remains problematic due to inter-laboratory di...