Using Artificial Intelligence to Diagnose Blood Diseases

Artificial intelligence has the potential to boost the method of diagnosing blood diseases using optical microscopes, according to a finding in the journal Blood. Every day, cytologists around the world use optical microscopes to analyze and classify blood cells. This method to diagnose blood diseases was established more than 150 years ago, is both a laborious and time-consuming task.

To overcome this, researchers developed the largest open-access database on microscopic images of bone marrow cells to date. The database consists of more than 170,000 single-cell images from over 900 patients with various blood diseases.

“On top of our database, we have developed a neural network that outperforms previous machine learning algorithms for cell classification in terms of accuracy, but also terms of generalizability,” says Christian Matek, lead author of the new study.

The deep neural network is a machine learning concept specifically designed to process images. The analysis of bone marrow cells has not yet been performed with such advanced neural networks. This is because high-quality, public datasets have not been available until now.

Researchers are now aiming to expand their bone marrow cell database further to capture a broader range of findings and to prospectively validate their model.

The database and the model are freely available for research and training purposes – to educate professionals or as a reference for further AI-based approaches e.g. in blood cancer diagnostics.

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Source-Medindia