Authors:
Yousra El Alaoui
1
;
Regina Padmanabhan
1
;
Adel Elomri
1
;
Halima El Omri
2
and
Abdelfatteh El Omri
3
Affiliations:
1
College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar
;
2
National Center for Cancer Care and Research, Hamad Medical Corporation, Doha, Qatar
;
3
Surgical Research Section, Department of Surgery, Hamad Medical Corporation, Doha, Qatar
Keyword(s):
Cancer Research, Machine Learning, Hematology Management.
Abstract:
Today, medical artificial intelligence (AI) applications are being extensively utilized to enhance the outcomes of clinical diagnosis and overall patient care. This data-driven approach can be trained to account for individuals’ unique characteristics, medical history, ethnicity, and even genetic make-up to obtain accurately tailored treatment recommendations. Given the power of medical AI, the severe nature of hematological malignancies and the related constraints in terms of both time and cost, in this paper, we are investigating the importance of AI applications in hematology management, with an illustration of AI’s role in reducing pre-and post-diagnosis challenges. Insights discussed here are derived based on our experiments on clinical datasets from National Center for Cancer Care & Research (NCCCR), Qatar. Specifically, we developed AI models for blood cancer diagnosis as well as prediction of therapy-induced clinical complications in patients with hematological cancers to fac
ilitate better hospital management and improved cancer care.
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