Single-cell microfluidic impedance cytometry: From raw signals to cell phenotypes using data analytics
The biophysical analysis of single-cells by microfluidic impedance cytometry is emerging as
a label-free and high-throughput means to stratify the heterogeneity of cellular systems …
a label-free and high-throughput means to stratify the heterogeneity of cellular systems …
Recent advances of utilizing artificial intelligence in lab on a chip for diagnosis and treatment
Nowadays, artificial intelligence (AI) creates numerous promising opportunities in the life
sciences. AI methods can be significantly advantageous for analyzing the massive datasets …
sciences. AI methods can be significantly advantageous for analyzing the massive datasets …
Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning approaches with impedance cytometry
Unrestricted cell death can lead to an immunosuppressive tumor microenvironment, with
dysregulated apoptotic signaling that causes resistance of pancreatic cancer cells to …
dysregulated apoptotic signaling that causes resistance of pancreatic cancer cells to …
Deciphering impedance cytometry signals with neural networks
Microfluidic impedance cytometry is a label-free technique for high-throughput single-cell
analysis. Multi-frequency impedance measurements provide data that allows full …
analysis. Multi-frequency impedance measurements provide data that allows full …
A review on microfluidics-based impedance biosensors
Electrical impedance biosensors are powerful and continuously being developed for various
biological sensing applications. In this line, the sensitivity of impedance biosensors …
biological sensing applications. In this line, the sensitivity of impedance biosensors …
Solid-state nanopore platform integrated with machine learning for digital diagnosis of virus infection
A Arima, M Tsutsui, T Washio, Y Baba… - Analytical …, 2020 - ACS Publications
The history of viruses in human society can never be taught without the history of detection
and treatment. As an ancient example, Egyptian mummies have been found to have scars …
and treatment. As an ancient example, Egyptian mummies have been found to have scars …
Exploiting machine learning for bestowing intelligence to microfluidics
Intelligent microfluidics is an emerging cross-discipline research area formed by combining
microfluidics with machine learning. It uses the advantages of microfluidics, such as high …
microfluidics with machine learning. It uses the advantages of microfluidics, such as high …
A neural network approach for real-time particle/cell characterization in microfluidic impedance cytometry
Microfluidic applications such as active particle sorting or selective enrichment require
particle classification techniques that are capable of working in real time. In this paper, we …
particle classification techniques that are capable of working in real time. In this paper, we …
Deep learning for non-parameterized MEMS structural design
The geometric designs of MEMS devices can profoundly impact their physical properties
and eventual performances. However, it is challenging for researchers to rationally consider …
and eventual performances. However, it is challenging for researchers to rationally consider …
[HTML][HTML] Advancing healthcare: synergizing biosensors and machine learning for early cancer diagnosis
Cancer is a fatal disease and a significant cause of millions of deaths. Traditional methods
for cancer detection often have limitations in identifying the disease in its early stages, and …
for cancer detection often have limitations in identifying the disease in its early stages, and …