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Label-free bacteria identification for clinical applications
Eliran Dafna,
Israel Gannot
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Corresponding author for this work
Department of Bio-Medical Engineering
Ben-Gurion University of the Negev
Optical Diagnostics
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Keyphrases
Absorption Spectroscopy
50%
Bacteria Identification
100%
Bacteria Types
100%
Clinical Application
100%
Clinical Microbiology Laboratory
50%
Clinical Setting
50%
Common Bacteria
50%
Convolution Operation
50%
Deep Learning Algorithm
50%
Ease of Operation
50%
Free Bacteria
100%
Label-free
100%
Mid-infrared
50%
Neural Network
50%
Nonlinear Operation
50%
One-dimensional Signal
50%
Probability Score
50%
Scale Feature
50%
Spectral Range
50%
System Accuracy
50%
System Sensitivity
50%
Engineering
Clinical Application
100%
Collected Data
100%
Deep Learning
100%
Macroscale
100%
Microscale
100%
Model Parameter
100%
Network Model
100%
One Dimensional
100%
Scale Feature
100%
Signal Output
100%
Signal Vector
100%
Spectral Range
100%
System Sensitivity
100%
Computer Science
Clinical Application
100%
Clinical Setting
100%
Collected Data
100%
Deep Learning
100%
Neural Network Model
100%
Postprocessing
100%
Physics
Absorption Spectroscopy
100%
Deep Learning
100%
Label-Free
100%
Neural Network
100%