Optimal Feature Selection from High-dimensional Fusion of Blood Smear Images for Leukemia Diagnosis
G. Chinna Pullaiah,
Ashok Kumar P.M.
Abstract:The goal of this study is to improve blood smear image-based blood cancer prediction through medical diagnostic advancements. Blood cancers, particularly leukemia, are challenging to diagnose because of the complexity of biological data and the dimensionality of medical images. There are interpretability and computational problems with each currently in use. We suggest the Random Forest-Recurrent Feature Elimination (RF-RFE) model to increase the precision and dependability of blood cancer diagnosis. This mode… Show more
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