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A Discussion of Machine Learning Approaches for Clinical Prediction Modeling

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Machine Learning in Clinical Neuroscience

Part of the book series: Acta Neurochirurgica Supplement ((NEUROCHIRURGICA,volume 134))

Abstract

While machine learning has occupied a niche in clinical medicine for decades, continued method development and increased accessibility of medical data have led to broad diversification of approaches. These range from humble regression-based models to more complex artificial neural networks; yet, despite heterogeneity in foundational principles and architecture, the spectrum of machine learning approaches to clinical prediction modeling have invariably led to the development of algorithms advancing our ability to provide optimal care for our patients. In this chapter, we briefly review early machine learning approaches in medicine before delving into common approaches being applied for clinical prediction modeling today. For each, we offer a brief introduction into theory and application with accompanying examples from the medical literature. In doing so, we present a summarized image of the current state of machine learning and some of its many forms in medical predictive modeling.

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Notes

  1. 1.

    Reinforcement learning, a third subcategory, is not discussed here.

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Authors and Affiliations

  1. Department of Neurosurgery, Stanford University, Stanford, CA, USA

    Michael C. Jin, Adrian J. Rodrigues, Michael Jensen & Anand Veeravagu

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  1. Michael C. Jin
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  2. Adrian J. Rodrigues
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  3. Michael Jensen
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  4. Anand Veeravagu
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Correspondence to Michael C. Jin or Anand Veeravagu .

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Editors and Affiliations

  1. Machine Intelligence in Clinical Neuroscience (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland

    Victor E. Staartjes

  2. Machine Intelligence in Clinical Neuroscience (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland

    Luca Regli

  3. Machine Intelligence in Clinical Neuroscience (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland

    Carlo Serra

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Jin, M.C., Rodrigues, A.J., Jensen, M., Veeravagu, A. (2022). A Discussion of Machine Learning Approaches for Clinical Prediction Modeling. In: Staartjes, V.E., Regli, L., Serra, C. (eds) Machine Learning in Clinical Neuroscience. Acta Neurochirurgica Supplement, vol 134. Springer, Cham. https://doi.org/10.1007/978-3-030-85292-4_9

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  • DOI: https://doi.org/10.1007/978-3-030-85292-4_9

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