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The integration of artificial intelligence (AI) into routine clinical practice is poised to revolutionize the diagnosis and treatment of hematologic diseases. AI-based models are already capable of automatically identifying cell populations including malignant cells, and facilitating early disease detection and prognosis. However, the efficacy of these tools depends on their correct application and interpretation, and hematologists need a basic understanding of machine learning to use AI effectively. In order to exploit the full potential of AI in hematologic diagnostics and to achieve a comprehensive integration of AI-based systems in routine clinical settings, there are challenges and limitations to be solved, including i.e. standardization of the methods, regulatory guidelines and training related questions. In this episode, we will dive into the current status and future directions of using AI in hematology. Oscar Brück, MD, PhD, is guest. He leads the Hematoscope Lab at the Helsinki University Hospital Comprehensive Cancer Center & Center of Diagnostics and the University of Helsinki. His team combines high-resolution imaging, big data, and machine learning to revolutionize the diagnosis and monitoring of hematological diseases. With a multidisciplinary expertise and approach, the group aims to harness technology to tackle cancer heterogeneity.

MAT-BE-2500595 (ver.1) 05 2025