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VOL. 4, ISSUE 1 (2022)
Advanced computational oncology: A systematic review of deep learning methods for carcinoma detection
Authors
Priyadarshini SRP, Sivaramarajalu Ramadurai Venkataraajalu
Abstract
Cancer remains a leading cause of morbidity and mortality globally,
necessitating advancements in diagnostic techniques for timely and accurate
identification of cancer cells. Deep learning, a subset of artificial
intelligence, has emerged as a revolutionary approach in medical imaging,
offering significant improvements in the detection and classification of
cancerous cells. This systematic review aims to comprehensively evaluate the
current literature on the application of deep learning techniques in the
identification of cancer cells. We analyze various deep learning methodologies,
datasets, performance metrics, and the associated challenges. By synthesizing
findings from recent studies, we highlight the potential of deep learning to
transform cancer diagnostics, discuss the robustness and interpretability of
these models, and identify areas for future research. Our review underscores
the promise of deep learning in enhancing diagnostic accuracy, reducing
workload for pathologists, and ultimately improving patient outcomes.
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Pages:65-70
How to cite this article:
Priyadarshini SRP, Sivaramarajalu Ramadurai Venkataraajalu "Advanced computational oncology: A systematic review of deep learning methods for carcinoma detection". International Journal of Medical Science and Research, Vol 4, Issue 1, 2022, Pages 65-70
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