Artificial intelligence for precision oncology: beyond patient stratification

Francisco Azuaje*

*Corresponding author for this work

    Research output: Contribution to journalReview articlepeer-review

    93 Citations (Scopus)


    The data-driven identification of disease states and treatment options is a crucial challenge for precision oncology. Artificial intelligence (AI) offers unique opportunities for enhancing such predictive capabilities in the lab and the clinic. AI, including its best-known branch of research, machine learning, has significant potential to enable precision oncology well beyond relatively well-known pattern recognition applications, such as the supervised classification of single-source omics or imaging datasets. This perspective highlights key advances and challenges in that direction. Furthermore, it argues that AI’s scope and depth of research need to be expanded to achieve ground-breaking progress in precision oncology.

    Original languageEnglish
    Article number6
    Journalnpj Precision Oncology
    Issue number1
    Publication statusPublished - 1 Dec 2019


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