Intelligent Blood Cell Recognition and Classification Using Deep Neural Networks
International Research Journal of Modernization in Engineering Technology and Science · 2025
It is an inseparable part of medical diagnosis in the sphere of hematology.Conventional methods of identifying and differentiating blood cells, though, have been both time consuming and labor intensive, and subject to human error.As artificial intelligence (AI) advances rapidly, particularly, one of its aspects, deep learning (DL), there is a chance to reshape this key aspect of healthcare.DL, or a sub-specialty of AI, applies multilayer models of artificial neural networks to understand complex patterns.In medicine, DL models can be trained to recognize and classify different kinds of cells, diseases or abnormalities with very high accuracy.Automation of the process of detecting and classifying blood cells will allow us to potentially increase the quality of diagnostic results, the structure of the applied DL models, and the performance measures.We shall also unveil the results and discuss them to interpret the strengths and weaknesses of the model and examine the implications of such findings on the future of automated hematology.The recent study may be considered as the step to further exploitation of artificial intelligence in medical labelling and shift to automated hematology in the future.