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Home > Machine Learning in Clinical Neuroscience: Foundations and Applications > Dimensionality Reduction: Foundations and Applications in Clinical Neuroscience
Machine Learning in Clinical Neuroscience: Foundations and Applications |
Victor E. Staartjes; Luca Regli; Carlo Serra
Springer International Publishing
Machine Learning in Clinical Neuroscience: Foundations and Applications
Dimensionality Reduction: Foundations and Applications in Clinical Neuroscience
Authors

Julius M. Kernbach; Jonas Ort; Karlijn Hakvoort; Hans Clusmann; Daniel Delev; Georg Neuloh

ARI Id

1665354112922_6064361

Access

Not Available Free

Pages

59-63

DOI

10.1007/978-3-030-85292-4_8

Chapter URL

https://rd.springer.com/chapter/10.1007/978-3-030-85292-4_8

Table of Contents of Book
Showing 1 to 20 of 45 entries
Chapters/HeadingsAuthor(s)PagesInfo
Front Matter
i-vii
Machine Intelligence in Clinical Neuroscience: Taming the Unchained Prometheus
Victor E. Staartjes; Luca Regli; Carlo Serra
1-4
Front Matter
5-5
Foundations of Machine Learning-Based Clinical Prediction Modeling: Part I—Introduction and General Principles
Julius M. Kernbach; Victor E. Staartjes
7-13
Foundations of Machine Learning-Based Clinical Prediction Modeling: Part II—Generalization and Overfitting
Julius M. Kernbach; Victor E. Staartjes
15-21
Foundations of Machine Learning-Based Clinical Prediction Modeling: Part III—Model Evaluation and Other Points of Significance
Victor E. Staartjes; Julius M. Kernbach
23-31
Foundations of Machine Learning-Based Clinical Prediction Modeling: Part IV—A Practical Approach to Binary Classification Problems
Victor E. Staartjes; Julius M. Kernbach
33-41
Foundations of Machine Learning-Based Clinical Prediction Modeling: Part V—A Practical Approach to Regression Problems
Victor E. Staartjes; Julius M. Kernbach
43-50
Foundations of Feature Selection in Clinical Prediction Modeling
Victor E. Staartjes; Julius M. Kernbach; Vittorio Stumpo; Christiaan H. B. van Niftrik; Carlo Serra; Luca Regli
51-57
Dimensionality Reduction: Foundations and Applications in Clinical Neuroscience
Julius M. Kernbach; Jonas Ort; Karlijn Hakvoort; Hans Clusmann; Daniel Delev; Georg Neuloh
59-63
A Discussion of Machine Learning Approaches for Clinical Prediction Modeling
Michael C. Jin; Adrian J. Rodrigues; Michael Jensen; Anand Veeravagu
65-73
Foundations of Bayesian Learning in Clinical Neuroscience
Gustav Burström; Erik Edström; Adrian Elmi-Terander
75-78
Introduction to Deep Learning in Clinical Neuroscience
Eddie de Dios; Muhaddisa Barat Ali; Irene Yu-Hua Gu; Tomás Gomez Vecchio; Chenjie Ge; Asgeir S. Jakola
79-89
Machine Learning-Based Clustering Analysis: Foundational Concepts, Methods, and Applications
Miquel Serra-Burriel; Christopher Ames
91-100
Deployment of Clinical Prediction Models: A Practical Guide to Nomograms and Online Calculators
Adrian E. Jimenez; James Feghali; Andrew T. Schilling; Tej D. Azad
101-108
Updating Clinical Prediction Models: An Illustrative Case Study
Hendrik-Jan Mijderwijk; Stefan van Beek; Daan Nieboer
109-113
Is My Clinical Prediction Model Clinically Useful? A Primer on Decision Curve Analysis
Hendrik-Jan Mijderwijk; Daan Nieboer
115-118
Front Matter
119-119
Introduction to Machine Learning in Neuroimaging
Julius M. Kernbach; Jonas Ort; Karlijn Hakvoort; Hans Clusmann; Georg Neuloh; Daniel Delev
121-124
Machine Learning Algorithms in Neuroimaging: An Overview
Vittorio Stumpo; Julius M. Kernbach; Christiaan H. B. van Niftrik; Martina Sebök; Jorn Fierstra; Luca Regli et al.
125-138
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 45 entries
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