Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning
- Book Chapter
With the biomedical field generating large quantities of time series data, there has been a growing interest in developing and refining machine learning methods that allow its mining and exploitation. Classification is one of the most important and challenging machine learning tasks related to time series. Many biomedical phenomena, such as the brain’s activity or blood pressure, change over time. The objective of this chapter is to provide a gentle introduction to time series classification. In the first part we describe the characteristics of time series data and challenges in its analysis. The second part provides an overview of common machine learning methods used for time series classification. A real-world use case, the early recognition of sepsis, demonstrates the applicability of the methods discussed. Show more
Book titleArtificial Neural Networks
Journal / seriesMethods in Molecular Biology
Pages / Article No.
SubjectTime series; Classification; Onset detection; Subsequence mining; Deep learning
Organisational unit09486 - Borgwardt, Karsten M. / Borgwardt, Karsten M.
MoreShow all metadata