Title | Artificial intelligence in oncology: From bench to clinic. |
Publication Type | Journal Article |
Year of Publication | 2022 |
Authors | Elkhader J, Elemento O |
Journal | Semin Cancer Biol |
Volume | 84 |
Pagination | 113-128 |
Date Published | 2022 Sep |
ISSN | 1096-3650 |
Keywords | Artificial Intelligence, Humans, Medical Oncology, Precision Medicine, Radiology, Reproducibility of Results |
Abstract | In the past few years, Artificial Intelligence (AI) techniques have been applied to almost every facet of oncology, from basic research to drug development and clinical care. In the clinical arena where AI has perhaps received the most attention, AI is showing promise in enhancing and automating image-based diagnostic approaches in fields such as radiology and pathology. Robust AI applications, which retain high performance and reproducibility over multiple datasets, extend from predicting indications for drug development to improving clinical decision support using electronic health record data. In this article, we review some of these advances. We also introduce common concepts and fundamentals of AI and its various uses, along with its caveats, to provide an overview of the opportunities and challenges in the field of oncology. Leveraging AI techniques productively to provide better care throughout a patient's medical journey can fuel the predictive promise of precision medicine. |
DOI | 10.1016/j.semcancer.2021.04.013 |
Alternate Journal | Semin Cancer Biol |
PubMed ID | 33915289 |
Grant List | F31 LM013058 / LM / NLM NIH HHS / United States R01 CA194547 / CA / NCI NIH HHS / United States U24 CA210989 / CA / NCI NIH HHS / United States P50 CA211024 / CA / NCI NIH HHS / United States UL1 TR002384 / TR / NCATS NIH HHS / United States |