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Unlocking the Potential of Artificial Intelligence in Acute Myeloid Leukemia and Myelodysplastic Syndromes

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Abstract

Purpose of the Review

This review aims to elucidate the transformative impact and potential of machine learning (ML) in the diagnosis, prognosis, and clinical management of myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). It further aims to bridge the gap between current advances of ML and their practical application in these diseases.

Recent Findings

Recent advances in ML have revolutionized prognostication, diagnosis, and treatment of MDS and AML. ML algorithms have proven effective in predicting disease progression, optimizing treatment responses, and in the stratification of patient groups. Particularly, the use of ML in genomic and epigenomic data analysis has unveiled novel insights into the molecular heterogeneity of MDS and AML, leading to better-informed therapeutic strategies. Furthermore, deep learning techniques have shown promise in analyzing complex patterns in bone marrow biopsy images, providing a potential pathway towards early and accurate diagnosis.

Summary

While still in the nascent stages, ML applications in MDS and AML signify a paradigm shift towards precision medicine. The integration of ML with traditional clinical practices could potentially enhance diagnostic accuracy, refine risk stratification, and improve therapeutic approaches. However, challenges related to data privacy, standardization, and algorithm interpretability must be addressed to realize the full potential of ML in this field. Future research should focus on the development of robust, transparent ML models and their ethical implementation in clinical settings.

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Authors and Affiliations

  1. Medical School, University of Jordan, Amman, Jordan

    Abdulrahman Alhajahjeh

  2. Department of Internal Medicine, King Hussein Cancer Center, Amman, Jordan

    Abdulrahman Alhajahjeh

  3. Department of Medical Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA

    Aziz Nazha

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  1. Abdulrahman Alhajahjeh
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Correspondence to Aziz Nazha.

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AN is an employee at Incyte Pharma and owns stock at Incyte.

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Alhajahjeh, A., Nazha, A. Unlocking the Potential of Artificial Intelligence in Acute Myeloid Leukemia and Myelodysplastic Syndromes. Curr Hematol Malig Rep 19, 9–17 (2024). https://doi.org/10.1007/s11899-023-00716-5

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  • DOI: https://doi.org/10.1007/s11899-023-00716-5

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