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AIM and Brain Tumors

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Artificial Intelligence in Medicine

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Abstract

Brain tumors are among the deadliest human cancers, and despite decades of intensive research the survival for many types of malignant primary brain tumors has not improved significantly. Since we continuously generate enormous amounts of clinical data of various modalities that help clinicians not only diagnose brain tumors, but also monitor, quantify, and assess the treatment process, implementing data-driven approaches to analyze such complex data automatically is becoming extremely important. In this chapter, we review artificial intelligence (Al)-powered approaches for this task, and discuss how AI can bring value into the clinical setting through automating tedious data analysis tasks, and extracting information from medical data that may directly affect the treatment pathway.

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Acknowledgments

This chapter is in memory of Dr. Grzegorz Nalepa, an extraordinary scientist and pediatric hematologist/oncologist at Riley Hospital for Children, Indianapolis, USA, who helped countless patients and their families through the most challenging moments of their lives.

The work was supported by the Silesian University of Technology grant for maintaining and developing research potential, and by Rectors Research and Development Grant 02/080/RGJ20/0003. The author thanks Krzysztof Kotowski for implementing the RANO visualization.

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Authors and Affiliations

  1. Silesian University of Technology, Gliwice, Poland

    Jakub Nalepa

  2. Future Processing Healthcare, Gliwice, Poland

    Jakub Nalepa

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  1. Jakub Nalepa
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Correspondence to Jakub Nalepa .

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  1. Karolinska Institute, Stockholm, Sweden

    Niklas Lidströmer

  2. Faculty of Medicine, Imperial College London, London, UK

    Hutan Ashrafian

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Nalepa, J. (2021). AIM and Brain Tumors. In: Lidströmer, N., Ashrafian, H. (eds) Artificial Intelligence in Medicine. Springer, Cham. https://doi.org/10.1007/978-3-030-58080-3_284-1

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  • DOI: https://doi.org/10.1007/978-3-030-58080-3_284-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58080-3

  • Online ISBN: 978-3-030-58080-3

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