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The Application of Artificial Intelligence to Cancer Research: A Comprehensive Guide.
Zadeh Shirazi, Amin; Tofighi, Morteza; Gharavi, Alireza; Gomez, Guillermo A.
Affiliation
  • Zadeh Shirazi A; Centre for Cancer Biology, SA Pathology and the University of South Australia, Adelaide, SA, Australia.
  • Tofighi M; Department of Electrical Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.
  • Gharavi A; Department of Computer Science, Azad University, Mashhad Branch, Mashhad, Iran.
  • Gomez GA; Centre for Cancer Biology, SA Pathology and the University of South Australia, Adelaide, SA, Australia.
Technol Cancer Res Treat ; 23: 15330338241250324, 2024.
Article in En | MEDLINE | ID: mdl-38775067
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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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Artificial Intelligence / Neoplasms Limits: Humans Language: En Journal: Technol Cancer Res Treat Journal subject: NEOPLASIAS / TERAPEUTICA Year: 2024 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Artificial Intelligence / Neoplasms Limits: Humans Language: En Journal: Technol Cancer Res Treat Journal subject: NEOPLASIAS / TERAPEUTICA Year: 2024 Document type: Article Affiliation country: Country of publication: