Biomedical Image Classification in a Big Data Architecture Using Machine Learning Algorithms

Table 2

Some ML methods and application comparison.

Authors	Deep learning methods	Machine learning method	Big data technologies	Applications
Luo et al. [2]	No	No	Yes (Hadoop)	Healthcare
Tchagna Kouanou et al. [7]	No	No	Yes (Spark and Hadoop)	Biomedical images
Manogaran and Lopez [8]	No	Yes	Yes	Healthcare
Thrall et al. [17]	No	Yes	No	Radiology
Fujiyoshi et al. [24]	Yes	No	No	Image recognition
Tchagna Kouanou et al. [77]	No	Yes (K-Means- unsupervised learning)	No	Biomedical image compression
Tchagna Kouanou et al. [78]	No	Yes (K-Means- unsupervised learning)	Yes (Hadoop)	Biomedical image compression
Tchagna Kouanou et al. [79]	No	Yes (K-Means- unsupervised learning)	No	Image compression
Alla Takam et al. [80]	Yes (CNN)	No	Yes (Spark)	Biomedical image
Chowdhary and Acharjya [81]	No	Yes (fuzzy C-means)	No	Feature extraction and segmentation
Bhattacharya et al. [82]	Yes	No	No	Biomedical image
Chowdhary et al. [83]	Yes	No	No	Biomedical images (breast cancer classification)
Wang et al. [84]	Yes (CNN, hierarchical loss)	No	No	Biomedical images (breast cancer classification)