An overview of artificial intelligence in oncology

• Published in: Future science OA Vol. 8; no. 4; p. FSO787
• Main Authors: Farina, Eduardo, Nabhen, Jacqueline J, Dacoregio, Maria Inez, Batalini, Felipe, Moraes, Fabio Y
• Format: Journal Article
• Language: English
• Published: England Future Science Ltd 01.04.2022; Taylor & Francis Group
• Subjects: artificial intelligence; cancer diagnosis; data integration; medical oncology; patient stratification; precision oncology; Review; medical oncology; precision oncology; cancer diagnosis; patient stratification; data integration; artificial intelligence
• ISSN: 2056-5623; 2056-5623
• DOI: 10.2144/fsoa-2021-0074

Cancer is associated with significant morbimortality globally. Advances in screening, diagnosis, management and survivorship were substantial in the last decades, however, challenges in providing personalized and data-oriented care remain. Artificial intelligence (AI), a branch of computer science used for predictions and automation, has emerged as potential solution to improve the healthcare journey and to promote precision in healthcare. AI applications in oncology include, but are not limited to, optimization of cancer research, improvement of clinical practice (eg., prediction of the association of multiple parameters and outcomes – prognosis and response) and better understanding of tumor molecular biology. In this review, we examine the current state of AI in oncology, including fundamentals, current applications, limitations and future perspectives. Cancer is associated with significant morbimortality globally. Although significant advances occurred in the last decades, challenges in providing personalized care remain. Artificial intelligence (AI) has emerged as a mean of improving cancer care using compure science. AI applications in oncology include, but are not limited to, optimization of cancer research, improvement of clinical practice (including prediction of cancer patients outcomes and response to treatment) and better understanding of tumor characteristics. In this review, we explored the current state of AI in oncology, including fundamentals, current applications, limitations and future perspectives.