Paper Contents
Abstract
Leukemia, a life-threatening hematologic disorder, demands rapid and accurate diagnostic methods for effective treatment. Conventional methods like manual blood smear analysis, flow cytometry, and molecular testing are time-consuming, error-prone, and require specialized expertise, often leading to diagnostic delays. To mitigate these issues, HemoDetect integrates advanced Artificial Intelligence (AI) and Machine Learning (ML) algorithms to automate leukemia detection. By processing blood smear images, extracting cellular features, and classifying abnormal cells using deep learning models, HemoDetect significantly enhances diagnostic precision and efficiency. The platform reduces reliance on manual analysis, offering a scalable, costeffective, and faster solution, particularly for resource-limited healthcare settings.
Copyright
Copyright © 2025 M.Yalinisathiya. This is an open access article distributed under the Creative Commons Attribution License.
