1. Evaluation of the performance of pre-trained CNN based DL model as feature

extractors towards classifying the parasitized and uninfected cells to aid in

improve disease training;

a. Presentation of comparative analysis of performance of customized and pre-

trained DL models as feature extractors toward classifying parasitized and

b. Cross validating the performance of predictive models at the patient level to

reduce bias and generalization errors,

c. Analysis and selection of optimal layers in pre-trained models to extract

features from underlying data and testing for the presence/absence of

statistically significant difference in performance of customized and pre-

trained CNN models under study.

2. Use of machine learning algorithms such as CNN and k-NN as claimed in 1 for classifying the cells.