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Artificial Intelligence-Aided Microfluidic Cell Culture Systems
Muhammad Sohail Ibrahim
, Minseok Kim
*
*
Corresponding author for this work
Interdisciplinary Research Center for Intelligent Secure Systems
Research output
:
Contribution to journal
›
Review article
›
peer-review
5
Scopus citations
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Computer Science
Artificial Intelligence
100%
Deep Learning Method
28%
System on a Chip
28%
Preprocessing
28%
Feature Extraction
28%
Feature Selection
14%
Privacy Preserving
14%
Dimensionality Reduction
14%
Inference Model
14%
Reproducibility
14%
Explainable Artificial Intelligence
14%
Technical Framework
14%
Autonomous System
14%
Decision-Making
14%
Technical Challenge
14%
Precision Medicine
14%
Disease Progression
14%
Machine Learning
14%
Learning System
14%
Optical Spectrum
14%
Immunology and Microbiology
Cell Culture
100%
Artificial Intelligence
100%
Feature Extraction
28%
Drug Screening
28%
Organoid
28%
Decision Making
14%
Tumor Spheroid
14%
Drug Response
14%
Exosome
14%
Angiogenesis
14%
Physiological Process
14%
Tissue Level
14%
Microorganism Detection
14%
Explainable Artificial Intelligence
14%
Engineering
Artificial Intelligence
100%
Feature Extraction
28%
Organoid
28%
Deep Learning Method
28%
Closed Loop
14%
Biochemicals
14%
Microbial
14%
Progression
14%
Dimensionality
14%
Technical Challenge
14%
Optical Spectrum
14%
Derived Cell
14%
Hydrogel
14%
Level Function
14%
High Resolution
14%
Autonomous System
14%
Learning System
14%
Real time control
14%
Explainable Artificial Intelligence
14%
Chemical Engineering
Exosome
14%
Biochemistry, Genetics and Molecular Biology
Biological Interpretation
12%