High‐Throughput, Living Single‐Cell, Multiple Secreted Biomarker Profiling Using Microfluidic Chip and Machine Learning for Tumor Cell Classification
Chao Wang(Hebei University of Engineering), Lin Han(Shenyang Ligong University), Yingkuan Han(Shandong University), Le Qiang(Shandong University), Yujin Chu(Shandong University), Xiaowei Shao(Shandong University), Yu Zhang(Shandong University), Chunhua Wang(Tzu Chi University), Jianwei Gao(Shandong University), Yihe Wang(Shandong University), Yu Wu(Peking University), Yanhao Wang(Chinese Academy of Sciences), Fangteng Song(Shandong University), Jiaoyan Qiu(Shandong University), Yakun Gao(Shandong University)
Cited by 54
Related Papers
Power Control in D2D-Based Vehicular Communication Networks
|IEEE Transactions on Vehicular Technology|2015|146
Not All Coverage Measurements Are Equal: Fuzzing by Coverage Accounting for Input Prioritization
|Unknown|2020|134
Mechanoluminescence enhancement of ZnS:Cu,Mn with piezotronic effect induced trap-depth reduction originated from PVDF ferroelectric film
|Nano Energy|2019|89
Analysis of the Influence of Foggy Weather Environment on the Detection Effect of Machine Vision Obstacles
|Sensors|2020|67
Microfluidic Biochips for Single‐Cell Isolation and Single‐Cell Analysis of Multiomics and Exosomes
|Advanced Science|2024|66