Artificial intelligence in oncology: From bench to clinic. Review uri icon

Overview

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.

publication date

  • April 26, 2021

Research

keywords

  • Artificial Intelligence
  • Radiology

Identity

Scopus Document Identifier

  • 85104941161

Digital Object Identifier (DOI)

  • 10.1016/j.semcancer.2021.04.013

PubMed ID

  • 33915289

Additional Document Info

volume

  • 84