Hematologic Cancer Detection Using White Blood Cancerous Cells Empowered with Transfer Learning and Image Processing

Table 9

Statistical matrix test results of blood cancer prediction after image processing (this depicts the statistical results of all models performed in the current study).

AlexNet
Stochastic gradient descent moment (%)
CA	Sen	PPV	FPR	FNR	LPR	LNR	FMI	F1	NPV	Spec	MCR
97.3	96.51	98.76	0.60	3.49	160.10	0.04	97.63	97.62	98.28	99.40	2.7
Adaptive moment estimation (%)
CA	Sen	PPV	FPR	FNR	LPR	LNR	FMI	F1	NPV	Spec	MCR
93.07	90.47	95.87	1.94	9.53	46.58	0.10	93.13	93.09	95.37	98.06	6.03
Root mean square propagation (%)
CA	Sen	PPV	FPR	FNR	LPR	LNR	FMI	F1	NPV	Spec	MCR
93.02	95.84	91.54	4.42	4.16	21.68	0.04	93.66	93.64	97.87	95.58	6.08
MobileNet
Stochastic gradient descent moment (%)
CA	Sen	PPV	FPR	FNR	LPR	LNR	FMI	F1	NPV	Spec	MCR
60.5	91.01	88.77	6.12	8.99	14.86	0.10	89.58	89.56	95.42	93.88	39.5
Adaptive moment estimation (%)
CA	Sen	PPV	FPR	FNR	LPR	LNR	FMI	F1	NPV	Spec	MCR
63.0	90.74	98.83	0.54	9.26	46.55	0.09	94.70	94.61	95.42	99.46	37.0
Root mean square propagation (%)
CA	Sen	PPV	FPR	FNR	LPR	LNR	FMI	F1	NPV	Spec	MCR
64.09	97.85	96.43	1.82	2.15	53.86	0.02	97.14	97.14	98.92	98.18	35.01
ResNet
Stochastic gradient descent moment (%)
CA	Sen	PPV	FPR	FNR	LPR	LNR	FMI	F1	NPV	Spec	MCR
66.2	96.24	99.86	0.07	3.76	30.15	0.04	98.03	98.02	98.92	99.93	83.8
Adaptive moment estimation (%)
CA	Sen	PPV	FPR	FNR	LPR	LNR	FMI	F1	NPV	Spec	MCR
66.5	59.55	88.04	6.31	40.45	9.43	0.43	72.40	71.04	98.92	93.69	33.5
Root mean square propagation (%)
CA	Sen	PPV	FPR	FNR	LPR	LNR	FMI	F1	NPV	Spec	MCR
65.6	59.28	87.92	6.34	40.72	9.35	0.43	72.20	70.82	98.92	93.66	34.4