Acta neurochirurgica. Supplement
Jan 1, 2022
In this chapter, we describe the process of obtaining medical imaging data and its storage protocol. The authors also explain in a step-by-step approach how to extract and prepare the medical imaging data for machine learning algorithms. And finally,...
Acta neurochirurgica. Supplement
Jan 1, 2022
In the last decades, modern medicine has evolved into a data-centered discipline, generating massive amounts of granular high-dimensional data exceeding human comprehension. With improved computational methods, machine learning and artificial intelli...
Acta neurochirurgica. Supplement
Jan 1, 2022
Machine learning (ML) and artificial intelligence (AI) applications in the field of neuroimaging have been on the rise in recent years, and their clinical adoption is increasing worldwide. Deep learning (DL) is a field of ML that can be defined as a ...
Acta neurochirurgica. Supplement
Jan 1, 2022
Advancements in neuroimaging and the availability of large-scale datasets enable the use of more sophisticated machine learning algorithms. In this chapter, we non-exhaustively discuss relevant analytical steps for the analysis of neuroimaging data u...
Acta neurochirurgica. Supplement
Jan 1, 2022
Unsupervised learning, the task of clustering observations in such a way that observations within cluster are more similar than those assigned to other clusters is one the central tasks of data science. Its exploratory and descriptive nature make it ...
Acta neurochirurgica. Supplement
Jan 1, 2022
The use of deep learning (DL) is rapidly increasing in clinical neuroscience. The term denotes models with multiple sequential layers of learning algorithms, architecturally similar to neural networks of the brain. We provide examples of DL in analyz...
Acta neurochirurgica. Supplement
Jan 1, 2022
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...
Acta neurochirurgica. Supplement
Jan 1, 2022
Selecting a set of features to include in a clinical prediction model is not always a simple task. The goals of creating parsimonious models with low complexity while, at the same time, upholding predictive performance by explaining a large proportio...
Acta neurochirurgica. Supplement
Jan 1, 2022
This chapter goes through the steps required to train and validate a simple, machine learning-based clinical prediction model for any continuous outcome. We supply fully structured code for the readers to download and execute in parallel to this sect...
Acta neurochirurgica. Supplement
Jan 1, 2022
We illustrate the steps required to train and validate a simple, machine learning-based clinical prediction model for any binary outcome, such as, for example, the occurrence of a complication, in the statistical programming language R. To illustrate...