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Artificial Intelligence for Precision Oncology

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Computational Methods for Precision Oncology

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1361))

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.

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Authors and Affiliations

  1. Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Sherry Bhalla

  2. Department of Genetics and Genomic Sciences, Department of Oncological Sciences, Mount Sinai Icahn School of Medicine, New York, NY, USA

    Alessandro Laganà

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  1. Department of Genetics and Genomic Sciences, Department of Oncological Sciences, Mount Sinai Icahn School of Medicine, New York, NY, USA

    Alessandro Laganà

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Bhalla, S., Laganà, A. (2022). Artificial Intelligence for Precision Oncology. In: Laganà, A. (eds) Computational Methods for Precision Oncology. Advances in Experimental Medicine and Biology, vol 1361. Springer, Cham. https://doi.org/10.1007/978-3-030-91836-1_14

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