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

Table 11

Comparative analysis with previous studies (this depicts the comparative study of current research with previous research).

Publication	Image processing	Model	Dataset	Accuracy (%)	MCR (%)
Pansombut et al. [35]	No	CNN	Image (public)	80	20
Madhukar et al. [34]	No	SVM	Image (public)	93.5	6.5
Supardi et al. [33]	No	KNN	Image (public)	86	14
Patel and Mishra [32]	No	SVM	Image (public)	93.57	6.53
Laosai and Chamnongthai [31]	No	SVM	Image (public)	92	18
Faivdullah et al. [30]	No	SVM	Feature (public)	79.38	20.72
Setiawan et al. [29]	No	SVM, K-means	Image (public)	87	13
Kumar et al. [28]	No	KNN, Naïve Bayes, CNN	Image (public)	92.8	17.2
Loey et al. [27]	No	CNN, AlexNet	Image (public)	94.3	5.7
The proposed model	Yes	Transfer learning (AlexNet, ResNet, MobileNet)	Image (public, 10,000 instances)	97.3	2.7