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Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases
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, w...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Atlantis Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8432325/ https://www.ncbi.nlm.nih.gov/pubmed/34595462 http://dx.doi.org/10.2991/chi.k.201130.001 |
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author | Muhsen, Ibrahim N. Shyr, David Sung, Anthony D. Hashmi, Shahrukh K. |
author_facet | Muhsen, Ibrahim N. Shyr, David Sung, Anthony D. Hashmi, Shahrukh K. |
author_sort | Muhsen, Ibrahim N. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8432325 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Atlantis Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84323252021-09-29 Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases Muhsen, Ibrahim N. Shyr, David Sung, Anthony D. Hashmi, Shahrukh K. Clin Hematol Int Review 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. Atlantis Press 2020-12-21 /pmc/articles/PMC8432325/ /pubmed/34595462 http://dx.doi.org/10.2991/chi.k.201130.001 Text en © 2020 International Academy for Clinical Hematology. Publishing services by Atlantis Press International B.V. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ). |
spellingShingle | Review Muhsen, Ibrahim N. Shyr, David Sung, Anthony D. Hashmi, Shahrukh K. Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases |
title | Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases |
title_full | Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases |
title_fullStr | Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases |
title_full_unstemmed | Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases |
title_short | Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases |
title_sort | machine learning applications in the diagnosis of benign and malignant hematological diseases |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8432325/ https://www.ncbi.nlm.nih.gov/pubmed/34595462 http://dx.doi.org/10.2991/chi.k.201130.001 |
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