Artificial Intelligence in Haematologic Diagnostics: Current Applications and Future Perspectives

Abstract

Translate Article

Take Notes

Plain Language SummaryHaematology encompasses a wide variety of disorders affecting the blood and bone marrow. A diagnosis often requires multiple – and, with increased understanding of diseases, progressively complex – tests. Doctors and laboratory professionals are therefore exploring how artificial intelligence (AI) can help improve the way disorders of the blood and bone marrow are detected and understood, particularly how AI offers new ways to make this process faster and more accurate. This article reviews how AI is being used in several key areas of haematological laboratories. These include examining cells under a microscope, analysing patterns in cells using specialized machines (a method called Flow Cytometry), studying genetic changes, and measuring the ability of blood to form clots (a process called haemostasis). Some current uses of AI include automatically sorting different types of blood cells, identifying possible causes of anaemia (a condition where there are not enough healthy red blood cells), and quickly detecting certain types of leukaemia, a cancer of the blood. AI can also help reduce human error when analysing test results and speed up the processing of large genetic datasets. However, there are challenges. Many AI tools do not work well across different laboratories or have not been tested enough to be used in everyday practice. Currently and in the near future, AI is best used to support experts by handling some of the early steps in the testing process. Final decisions about a diagnosis still need to be made by trained professionals in blood diseases.