A Comprehensive Review on Leukemia Diseases Based on Microscopic Blood Cell Images
Della Reasa Valiaveetil, T Kanimozhi · 2023
Early prediction of leukemia minimizes the spread of tumor cells within the bloodstream. Despite other cancers, leukemia is categorized as aggressive cancer because of the problematic diagnosis. The current work is a systematic review of the leukemia diagnosis process. The study analyses the existing research and works on microscopic leukemia cells (MLCs), especially under machine learning (ML) and deep learning (DL) techniques. This chapter inspects the various ML and DL approaches for MLCs. The key objective of this chapter is to isolate and categorize effective ML and DL techniques for leukemia classification. It also states the common and crucial pitfalls of the existing systems. The survey analysis points out that the DL models work better on the classification process than other algorithms. Moreover, the classification accuracy of the DL technique ranges around 98.36%–99.57% in the hybrid network while the ML stays around 86%–92%. The survey concludes that DL network is the best option for leukemia classification under hybrid architecture.