Research from Southeast University Has Provided New Study Findings on Engineering (Automatic Classification of White Blood Cells Using a Semi-Supervised Convolutional Neural Network).

A recent study conducted by researchers at Southeast University in Nanjing, China, has developed a semi-supervised convolutional neural network for the automatic classification of white blood cells. Accurate classification of white blood cell subtypes is crucial for diagnosing blood diseases. The researchers found that their model achieved a high accuracy of 94.4% with only 500 labeled samples, demonstrating promising prospects for clinically useful solutions in detecting white blood cells based on blood cell images. This research provides valuable insights into the application of machine learning and emerging technologies in the field of hematology. [Extracted from the article]