Jeong‐Yeol Yoon

Microfluidic Sensors Integrated with Smartphones for Applications in Forensics, Agriculture, and Environmental Monitoring

Low-cost, multispectral machine learning classification of simulated airborne micro/nanoplastics

Soil microbiome characterization and its future directions with biosensing

A comparison of current analytical methods for detecting particulate matter and micro/nanoplastics

Receptor-based detection of microplastics and nanoplastics: Current and future

eXtreme gradient boosting-based classification of bacterial mixtures in water and milk using wireless microscopic imaging of quorum sensing peptide-conjugated particles

Recent Uses of Paper Microfluidics in Isothermal Nucleic Acid Amplification Tests

Capillary flow velocity profile analysis on paper-based microfluidic chips for screening oil types using machine learning

Smartphone-Based Microalgae Monitoring Platform Using Machine Learning

Rapid and sensitive detection of miRNA via light scatter-aided emulsion-based isothermal amplification using a custom low-cost device

Smartphone-based sensitive detection of SARS-CoV-2 from saline gargle samples via flow profile analysis on a paper microfluidic chip

Rapid, sensitive detection of PFOA with smartphone-based flow rate analysis utilizing competitive molecular interactions during capillary action

Microscopic Imaging Methods for Organ-on-a-Chip Platforms

Biosensor detection of airborne respiratory viruses such as SARS-CoV-2

Bioanalytical approaches for the detection, characterization, and risk assessment of micro/nanoplastics in agriculture and food systems

Progression of LAMP as a Result of the COVID-19 Pandemic: Is PCR Finally Rivaled?

Sensitive, smartphone-based SARS-CoV-2 detection from clinical saline gargle samples

Machine Learning-Based Quantification of (−)-<i>trans</i>-Δ-Tetrahydrocannabinol from Human Saliva Samples on a Smartphone-Based Paper Microfluidic Platform

Smartphone-based autofluorescence imaging to detect bacterial species on laboratory surfaces

Machine Learning Enhances the Performance of Bioreceptor-Free Biosensors

Norovirus detection in water samples at the level of single virus copies per microliter using a smartphone-based fluorescence microscope

In situ sensors for blood-brain barrier (BBB) on a chip

Human sensor-inspired supervised machine learning of smartphone-based paper microfluidic analysis for bacterial species classification

FEAST of biosensors: Food, environmental and agricultural sensing technologies (FEAST) in North America

Direct capture and smartphone quantification of airborne SARS-CoV-2 on a paper microfluidic chip

A guanidinium-rich polymer as a new universal bioreceptor for multiplex detection of bacteria from environmental samples

Natural killer cell detection, quantification, and subpopulation identification on paper microfluidic cell chromatography using smartphone-based machine learning classification

Environmental Toxicology Assays Using Organ-on-Chip

Proximal Methods for Plant Stress Detection Using Optical Sensors and Machine Learning

Smartphone based on-chip fluorescence imaging and capillary flow velocity measurement for detecting ROR1+ cancer cells from buffy coat blood samples on dual-layer paper microfluidic chip