Abstract

Precision oncology is an innovative approach to cancer care in which diagnosis, prognosis, and treatment are informed by the individual patient’s genetic and molecular profile. The rapid development of novel high-throughput omics technologies in recent years has led to the generation of massive amount of complex patient data, which in turn has prompted the development of novel computational infrastructures, platforms, and tools to store, retrieve, and analyze this data efficiently. Artificial intelligence (AI), and in particular its subfield of machine learning, is ideal for deciphering patterns in large datasets and offers unique opportunities for advancing precision oncology. In this chapter, we provide an overview of the various public data resources and applications of AI in precision oncology and cancer research, from subtype identification to drug prioritization, using multi-omics datasets. We also discuss the impact of AI-powered medical image analysis in oncology and present the first diagnostic FDA-approved AI-powered tools.

Original languageEnglish
Title of host publicationAdvances in Experimental Medicine and Biology
PublisherSpringer
Pages249-268
Number of pages20
DOIs
StatePublished - 2022

Publication series

NameAdvances in Experimental Medicine and Biology
Volume1361
ISSN (Print)0065-2598
ISSN (Electronic)2214-8019

Keywords

  • Artificial intelligence
  • Cancer
  • Cancer subtype
  • Deep learning
  • Drug prioritization
  • High-throughput technologies
  • Machine learning
  • Medical image analysis
  • Multi-omics
  • Precision oncology
  • Sequencing

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