Biomedical Approaches For Analyzing Blood Cells Based on Machine Learning

This paper introduces a whole new concept of scanning blood cells with an emphasis on industry to improve the image-processing, segmentation, and classification techniques. Cytologists mount the ability to view blood cells more thoroughly and unbiasedly may enable them by this technology to visually evaluate the structural features of the cells directly which is going to lead to a more accurate assessment. To help in the development of new technologies like deep learning methods, it is important that researchers and developers get access to a large library of cell photos from hospitals and laboratories. Those lymphocytes and blood cancer cell studies cannot be distinguished via the conditions of only their physical properties for the purpose of using the current technologies. Well-constructed screening procedures ought to apply a recognizing model as well as a testing method to confirm the data. One more step is to consider different classification techniques with hurdles to having patients’ say in the implementation process.

کلیدواژه ها:

biomedical applications ، machine learning ، deep learning ، neural networks ، IoT