Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases
- https://doi.org/10.2991/chi.k.201130.001How to use a DOI?
- Hematology, machine learning, artificial intelligence
The use of machine learning (ML) and deep learning (DL) methods in hematology includes diagnostic, prognostic, and therapeutic applications. This increase is due to the improved access to ML and DL tools and the expansion of medical data. The utilization of ML remains limited in clinical practice, with some disciplines further along in their adoption, such as radiology and histopathology. In this review, we discuss the current uses of ML in diagnosis in the field of hematology, including image-recognition, laboratory, and genomics-based diagnosis. Additionally, we provide an introduction to the fields of ML and DL, highlighting current trends, limitations, and possible areas of improvement.
- © 2020 International Academy for Clinical Hematology. Publishing services by Atlantis Press International B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Ibrahim N. Muhsen AU - David Shyr AU - Anthony D. Sung AU - Shahrukh K. Hashmi PY - 2020 DA - 2020/12 TI - Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases JO - Clinical Hematology International SN - 2590-0048 UR - https://doi.org/10.2991/chi.k.201130.001 DO - https://doi.org/10.2991/chi.k.201130.001 ID - Muhsen2020 ER -