Deep Learning for the Detection of Acute Lymphoblastic Leukemia Subtypes on Microscopic Images: A Systematic Literature Review

Computer vision research in detecting and classifying the subtype Acute Lymphoblastic Leukemia (ALL) has contributed to computer-aided diagnosis with improved accuracy. Another contribution is serve as an assistant second opinion for doctors hematologists diagnosing ALL subtype. Early detection can also rely on determine initial treatment. The purpose of this study review progress classification subtypes. method’s discussion focuses application deep learning domain object classification. Motivations, challenges, future recommendations are thoroughly discussed improve understanding field study. was carried out methodically by analyzing a collection papers subtypes published science direct, IEEE, PubMed from 2018 2022. analysis paper included results selected paper. selection among 65 based inclusion exclusion methods. Based methods objectives, divided into two large groups. first group discusses subtypes, while prior reveals some challenging issues work, such limited availability dataset, high computational complexity model, further exploration transformers computer reference gaps that contribute research.