Overview of Correction Huang Et Al Deep Learning Based Label Free
This corrects the article " Deep-Learning Based Label-Free Classification of Activated and Inactivated Neutrophils for Rapid Immune State Monitoring ", 512. The authors wish to make the following correction to their paper [1]:
Correction : Huang et al . Deep-Learning Based Label-Free Classification of Activated and Inactivated Neutrophils for Rapid Immune State Monitoring. Sensors 2021, 21, 512.
(PDF) Correction
This deep learning-based method for label-free WBC classification can tackle the problem of complex instrumental operation and interference of fluorescent labeling to the physiological states of ...
The authors wish to make the following correction to their paper [...].
PDF Correction
The authors wish to make the following correction to their paper [1]: Hyungkook Jeon and Jongyoon Han have been added as co-authors due to their contribution in processing blood samples using microfluidic blood sorting devices.
A deep learning-based method to perform label-free classification of three types of WBCs based on their morphologies to judge the activated or inactivated neutrophils is proposed, which is promising for future point-of-care applications.
Overview of Correction Huang Et Al Deep Learning Based Label Free
Correction : Huang et al . Deep-Learning Based Label-Free Classification of Activated and Inactivated Neutrophils for Rapid Immune State Monitoring. Sensors 2021, 21, 512.
Correction : Huang et al . Deep-Learning Based Label-Free Classification of Activated and Inactivated Neutrophils for Rapid Immune State Monitoring. Sensors 2021, 21, 512 - Science Explorer Abstract
Key Details About Correction Huang Et Al Deep Learning Based Label Free
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