Table 1 Performance of the proposed model in waveform, frequency spectrum, and spectrogram. A, \(F_1\), P, and R indicate accuracy, \(F_1\) score, precision, and recall, respectively. Avg. and S.D. refer to the mean and standard deviation of three folds, respectively.

From: Automated cell-type classification combining dilated convolutional neural networks with label-free acoustic sensing

PNT1A/RBC

Waveform

Frequency Spectrum

Spectrogram

A

\(F_1\)

P

R

A

\(F_1\)

P

R

A

\(F_1\)

P

R

1-Fold

0.97

0.98

1.00

0.96

0.96

0.97

0.97

0.97

0.98

0.99

1.00

0.97

2-Fold

0.97

0.98

0.97

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

3-Fold

0.97

0.64

0.63

0.67

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

Avg.

0.98

0.88

0.88

0.88

0.99

0.99

0.99

0.99

0.99

1.00

1.00

0.99

S.D.

0.02

0.20

0.22

0.18

0.02

0.02

0.02

0.02

0.01

0.01

0.00

0.02

SVM

0.76

0.76

0.76

0.76

0.86

0.86

0.86

0.86

0.96

0.96

0.96

0.96

Logit

0.74

0.74

0.74

0.75

0.78

0.78

0.79

0.79

0.96

0.96

0.96

0.96

MLP

0.78

0.78

0.78

0.78

0.92

0.92

0.92

0.92

0.51

0.51

0.51

0.51

  1. Models with the highest evaluation metrics are highlighted in [bold].