1. The Role of Machine Learning in the Most Common Hematological Malignancies: A Narrative Review
- Author
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Teresa Perillo, Marco de Giorgi, Claudia Giorgio, Carmine Frasca, Renato Cuocolo, and Antonio Pinto
- Subjects
hematological malignancies machine learning ,leukemia ,lymphoma ,multiple myeloma ,artificial intelligence ,Medicine - Abstract
Background: Hematologic malignancies are a group of heterogeneous neoplasms which originate from hematopoietic cells. The most common among them are leukemia, lymphoma, and multiple myeloma. Machine learning (ML) is a subfield of artificial intelligence that enables the analysis of large amounts of data, possibly finding hidden patterns. Methods: We performed a narrative review about recent applications of ML in the most common hematological malignancies. We focused on the most recent scientific literature about this topic. Results: ML tools have proved useful in the most common hematological malignancies, in particular to enhance diagnostic work-up and guide treatment. Conclusions: Although ML has multiple possible applications in this field, there are some issue that have to be fixed before they can be used in daily clinical practice.
- Published
- 2024
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