Blood Cancer Identification using Hybrid Ensemble Deep Learning Technique
J. Jayachitra, N. Umarkathaf · 2023
Blood cancer-related illnesses may be challenging to examine and diagnose, both of which can take a significant period of time. During the course of the preceding decade, a variety of methods for detecting, analysing, and categorizing blood cancer in people were established. These methods include: However, as of right now, there is neither a method nor a model available that can automate the process of inspecting human blood cells to determine whether or not cancer is present. A model with these characteristics has the potential to improve disease detection and prevention, which would lead to a prompter medical diagnosis. This study presents the research progress made in the area of Deep Learning Model to identify the abnormalities in blood cells. In order to detect blood cancer, this study has used Hybrid Ensemble Deep Learning method. This method results with an accuracy of more than 95%.