International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 6 Issue 5
September-October 2024
Indexing Partners
Artificial Intelligence and Machine Learning in Early Diagnosis of Hematological Malignancies
Author(s) | Imran Hussain, Ekta A Andriyas, Munzali Hamisu Umar, Arun Kumar Saxena |
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Country | India |
Abstract | In this Era of Machine Learning (ML) and Artificial Intelligence (AI), there is no field left in which these two have not left their impact. Blood cancer or Leukemia is now a days one of the very common hematological disorders. It is very difficult to diagnose leukemia in its very early stages, when it is diagnosed in its later stages it is very difficult to treat it because there are very limited treatments available. So, it is now very important to improve the diagnostic tools and techniques in traditional diagnostics procedures. ML and AI methods have recently garnered a great deal of attention in the field of cancer research by making a noticeable contribution to the growth of predictive medicine and modern oncological practices. Considerable focus has been particularly directed toward hematologic malignancies because of the complexity of detecting early symptoms. Many patients with blood cancer do not get properly diagnosed until their cancer has reached an unnumbered stage with limited treatment prospects. Hence, the state-of-the-art revolves around the latest artificial intelligence applications in hematology management. |
Keywords | Artificial Intelligence, Leukemia, Diagnosis, Machine Learning |
Field | Biology > Medical / Physiology |
Published In | Volume 6, Issue 1, January-February 2024 |
Published On | 2024-01-04 |
Cite This | Artificial Intelligence and Machine Learning in Early Diagnosis of Hematological Malignancies - Imran Hussain, Ekta A Andriyas, Munzali Hamisu Umar, Arun Kumar Saxena - IJFMR Volume 6, Issue 1, January-February 2024. DOI 10.36948/ijfmr.2024.v06i01.11627 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i01.11627 |
Short DOI | https://doi.org/gtdsb8 |
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