The application of artificial intelligence to cancer research: a comprehensive guide
Date
2024
Authors
Zadeh Shirazi, A.
Tofighi, M.
Gharavi, A.
Gomez, G.A.
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Journal article
Citation
Technology in Cancer Research & Treatment, 2024; 23:1-20
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Abstract
Advancements in AI have notably changed cancer research, improving patient care by enhancing detection, survival prediction, and treatment efficacy. This review covers the role of Machine Learning, Soft Computing, and Deep Learning in oncology, explaining key concepts and algorithms (like SVM, Naïve Bayes, and CNN) in a clear, accessible manner. It aims to make AI advancements understandable to a broad audience, focusing on their application in diagnosing, classifying, and predicting various cancer types, thereby underlining AI's potential to better patient outcomes. Moreover, we present a tabular summary of the most significant advances from the literature, offering a time-saving resource for readers to grasp each study's main contributions. The remarkable benefits of AI-powered algorithms in cancer care underscore their potential for advancing cancer research and clinical practice. This review is a valuable resource for researchers and clinicians interested in the transformative implications of AI in cancer care.
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Dissertation Note
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Description
Data source: Supplementary material, https://doi.org/10.1177/15330338241250324
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Copyright 2024 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 License, which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). (https://creativecommons.org/licenses/by/4.0/)