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The New Possibilities from “Big Data” to Overlooked Associations Between Diabetes, Biochemical Parameters, Glucose Control, and Osteoporosis

Current Osteoporosis Reports volume 16, pages 320–324 (2018)Cite this article

Abstract

Purpose of Review

To review current practices and technologies within the scope of “Big Data” that can further our understanding of diabetes mellitus and osteoporosis from large volumes of data. “Big Data” techniques involving supervised machine learning, unsupervised machine learning, and deep learning image analysis are presented with examples of current literature.

Recent Findings

Supervised machine learning can allow us to better predict diabetes-induced osteoporosis and understand relative predictor importance of diabetes-affected bone tissue. Unsupervised machine learning can allow us to understand patterns in data between diabetic pathophysiology and altered bone metabolism. Image analysis using deep learning can allow us to be less dependent on surrogate predictors and use large volumes of images to classify diabetes-induced osteoporosis and predict future outcomes directly from images.

Summary

“Big Data” techniques herald new possibilities to understand diabetes-induced osteoporosis and ascertain our current ability to classify, understand, and predict this condition.

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Authors and Affiliations

  1. Steno Diabetes Center North Jutland, Sdr. Skovvej 15, 9000, Aalborg, Denmark

    Christian Kruse

  2. Department of Clinical Medicine, Aalborg University, Sdr. Skovvej 15, 9000, Aalborg, Denmark

    Christian Kruse

  3. Department of Endocrinology, Aalborg University Hospital, Hobrovej 19, 9100, Aalborg, Denmark

    Christian Kruse

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  1. Christian Kruse
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Correspondence to Christian Kruse.

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This article is part of the Topical Collection on Bone and Diabetes

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Kruse, C. The New Possibilities from “Big Data” to Overlooked Associations Between Diabetes, Biochemical Parameters, Glucose Control, and Osteoporosis. Curr Osteoporos Rep 16, 320–324 (2018). https://doi.org/10.1007/s11914-018-0445-9

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  • DOI: https://doi.org/10.1007/s11914-018-0445-9

Keywords

  • Diabetes
  • Osteoporosis
  • Fractures
  • Glucose
  • Big data
  • Machine learning