Enhancing diagnostic accuracy of multiple myeloma through ml-driven analysis of hematological slides: new dataset and identification model to support hematologists

HIGHLIGHTS

• What: In this work, although the dataset is composed by images with different types of cells, supporting the investigation of several biological subjects, the authors have focused the attention to support the diagnosis of MM. Therefore, the labels of the cells were categorized into 1,891 "plasma cells" and 1,931 "non-plasma cells". The aim of this study is to investigate the automatic identification of plasma cells in images through the development of an ML-based approach. The primary challenge lies in devising an approach that aids specialists in the diagnosis of MM. Notably, the work . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.