DefinePK

Abstract

Objective: The objective of this review to investigate the role of AI in enhancing the efficiency of automated blood-cell counters for identifying different pathologies and reducing human errors.  Introduction: The whole blood count test is mostly performed by automated blood cell counters. However, it was less accurate sometimes and errors are also existed in this method. The integration of AI with machine learning (ML) and deep learning (DL) algorithms, enhances the performance of automated blood cell counters. Materials and Methods: The data of this article is collected from various well-known academic data bases after careful analysis of mostly articles published in the last 5 years. Results: AI incorporation into automated blood cell counters reduces manual work and the extra burden. The advanced image-analysis ability of these types of blood cell counters helps them to identify different types of morphological changes which helps in the early diagnosis of different types of leukemia and other blood cancers. Conclusion: Integrating AI into blood cell counts plays a significant role in diagnosis. These advancements are helpful for patients and laboratory professionals. Although there are some ethical challenges do exist in these advanced technologies. Continued innovations and validations are key components of the future of AI-based blood cell counts.