Role of Artificial Intelligence and Machine Learning in Haematology
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Machine Learning and Artificial Intelligence in Diagnostics".
Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 3524
Special Issue Editor
2. Program Director, Hematology Fellowship Program, Doha, Qatar
3. Associate Professor of Medicine, Qatar University, Doha, Qatar
4. National Center for Cancer Care and Research, Doha, Qatar
5. Hamad Medical Corporation, Doha, Qatar
Interests: hematology; oncology; insulin resistance; diabetes; cancer biology; cancer biomarkers; cancer research; flow cytometry; treatment; infection; health education
Special Issue Information
Dear Colleagues,
Digitalization of patients records and integration of genomic methods into clinical practice have resulted in an unprecedented wealth of data. Machine learning is part of artificial intelligence that attempts to computationally extract meaningful insights from complex data structures. Applications of machine learning in hematological scenarios are steadily increasing. There is both much hope and hype surrounding the application of machine learning in medicine. Terms such as artificial intelligence, precision medicine, machine learning and deep learning are becoming ever more frequent in the medical literature, Recent findings: AI has been employed in the analysis of hematopathological, radiographic, laboratory, genomic, pharmacological, and chemical data to better inform diagnosis, prognosis, treatment planning, and foundational knowledge related to benign and malignant hematology. Artificial intelligence techniques ranging from machine learning to deep learning are prevalent in healthcare for disease diagnosis, drug discovery, and patient risk identification. In this special issue, we would like to shed light on artificial intelligence and machine learning in Hematology.
Dr. Mohamed A. Yassin
Guest Editor
Manuscript Submission Information
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Keywords
- artificial intelligence
- machine learning
- hematology
- hematopathological
- benign and malignant hematology
