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The Application of AI in Precision Oncology: Tailoring Diagnosis, Treatment, and the Monitoring of Disease Progression to the Patient

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Artificial Intelligence and Precision Oncology

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Abstract

Personalised oncology has long been the ideal when it comes to the management of cancer. The ability to tailor screening, diagnosis, therapy and monitoring to an individual patient or group of patients would vastly decrease the burden of cancer while ensuring higher rates of patient survival and treatments with less side effects and more success in controlling or eliminating the disease. Precision oncology requires that as much information regarding the patient or population group be known. In terms of the underlying molecular basis of the disease, this is now being realised further to the advent of high throughput technologies such as next-generation sequencing (NGS) and advances in mass spectrophotometry. This has led to an “omics” revolution, with large datasets of information regarding the molecular basis of cancer in individuals being generated. Artificial intelligence (AI) is the ideal technology to manage and interpret these large datasets. In conjunction with machine learning (ML) and deep learning (DL), AI can more accurately interpret not only omics data, but it can also integrate data from other sources such as patient reports and medical imaging to give a more precise view of the individual or population, allowing for better clinical decision-making.

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  1. SAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChI Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Cancer Research Institute (PACRI), University of Pretoria, Pretoria, South Africa

    Zodwa Dlamini & Rodney Hull

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    Zodwa Dlamini

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Dlamini, Z., Hull, R. (2023). The Application of AI in Precision Oncology: Tailoring Diagnosis, Treatment, and the Monitoring of Disease Progression to the Patient. In: Dlamini, Z. (eds) Artificial Intelligence and Precision Oncology. Springer, Cham. https://doi.org/10.1007/978-3-031-21506-3_1

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