Machine learning in clinical neuroscience: foundations and applications
Preface -- Foundations of machine learning-based clinical prediction modeling - Part I: Introduction and general principles -- Foundations of machine learning-based clinical prediction modeling - Part II: Generalization and Overfitting -- Foundations of machine learning-based clinical prediction mod...
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| Other Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cham
Springer
[2022]
|
| Series: | Acta neurochirurgica supplement
134 |
| Subjects: | |
| Summary: | Preface -- Foundations of machine learning-based clinical prediction modeling - Part I: Introduction and general principles -- Foundations of machine learning-based clinical prediction modeling - Part II: Generalization and Overfitting -- Foundations of machine learning-based clinical prediction modeling - Part III: Evaluation and other points of significance -- Foundations of machine learning-based clinical prediction modeling - Part IV: A practical approach to binary classification problems -- Foundations of machine learning-based clinical prediction modeling - Part V: A practical approach to regression problems -- Supervised and unsupervised learning / clustering -- Introduction to Bayesian Modeling -- Introduction to Deep Learning -- Overview of algorithms for machine-learning based clinical prediction modelling -- Foundations of feature selection in clinical prediction modelling -- Dimensionality reduction: Foundations and applications in clinical neuroscience -- Machine learning-based survival modeling: Foundations and Applications -- Making clinical prediction models available: A brief introduction -- Machine Learning-based Clustering Analysis: Foundational Concepts, Methods, and Applications -- Introduction to Machine Learning in Neuroimaging -- Overview of machine learning algorithms in imaging -- Foundations of classification modeling based on neuroimaging -- Foundations of lesion-symptom mapping using machine learning -- Foundations of Machine Learning-Based Segmentation in Cranial Imaging -- Foundations of lesion detection using machine learning in clinical neuroimaging -- Foundations of multiparametric brain tumor imaging characterization -- Radiomics in clinical neuroscience – Overview -- Radiomic feature extraction: Methodological Foundations -- Complexity and interpretability in machine vision -- Foundations of intraoperative anatomical recognition using machine vision -- Machine Vision Foundations -- Natural Language Processing: Foundations and Applications in Clinical Neuroscience -- Foundations of Time Series Analysis -- Overview of algorithms for natural language processing and time series analysis -- History of machine learning in neurosurgery -- The AI doctor - considerations for AI-based medicine -- Ethics of Machine Learning-Based Predictive Analytics -- Predictive analytics in clinical practice: Pro and contra -- Review of machine vision applications in neuroophtalmology -- Prediction Model -- Prediction Model -- Prediction Model -- Topical Review of machine learning in intracranial aneurysm surgery -- Review of applications of machine learning in neuroimaging -- Prediction Model -- An overview of machine learning applications in the Neurointensive Care Unit -- Prediction Model -- Review of natural language processing in the clinical neurosciences -- Review of big data applications in the clinical neurosciences -- |
| Physical Description: | vii, 361 Seiten Illustrationen |
| ISBN: | 9783030852917 |
Staff View
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| 520 | 3 | |a Preface -- Foundations of machine learning-based clinical prediction modeling - Part I: Introduction and general principles -- Foundations of machine learning-based clinical prediction modeling - Part II: Generalization and Overfitting -- Foundations of machine learning-based clinical prediction modeling - Part III: Evaluation and other points of significance -- Foundations of machine learning-based clinical prediction modeling - Part IV: A practical approach to binary classification problems -- Foundations of machine learning-based clinical prediction modeling - Part V: A practical approach to regression problems -- Supervised and unsupervised learning / clustering -- Introduction to Bayesian Modeling -- Introduction to Deep Learning -- Overview of algorithms for machine-learning based clinical prediction modelling -- Foundations of feature selection in clinical prediction modelling -- Dimensionality reduction: Foundations and applications in clinical neuroscience -- | |
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| 520 | 3 | |a Natural Language Processing: Foundations and Applications in Clinical Neuroscience -- Foundations of Time Series Analysis -- Overview of algorithms for natural language processing and time series analysis -- History of machine learning in neurosurgery -- The AI doctor - considerations for AI-based medicine -- Ethics of Machine Learning-Based Predictive Analytics -- Predictive analytics in clinical practice: Pro and contra -- Review of machine vision applications in neuroophtalmology -- Prediction Model -- Prediction Model -- Prediction Model -- Topical Review of machine learning in intracranial aneurysm surgery -- Review of applications of machine learning in neuroimaging -- Prediction Model -- An overview of machine learning applications in the Neurointensive Care Unit -- Prediction Model -- Review of natural language processing in the clinical neurosciences -- Review of big data applications in the clinical neurosciences -- | |
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| illustrated | Illustrated |
| index_date | 2024-07-03T18:55:10Z |
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| institution | BVB |
| isbn | 9783030852917 |
| language | English |
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| spelling | Machine learning in clinical neuroscience foundations and applications Victor E. Staartjes, Luca Regli, Carlo Serra, editors Cham Springer [2022] vii, 361 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Acta neurochirurgica supplement 134 Preface -- Foundations of machine learning-based clinical prediction modeling - Part I: Introduction and general principles -- Foundations of machine learning-based clinical prediction modeling - Part II: Generalization and Overfitting -- Foundations of machine learning-based clinical prediction modeling - Part III: Evaluation and other points of significance -- Foundations of machine learning-based clinical prediction modeling - Part IV: A practical approach to binary classification problems -- Foundations of machine learning-based clinical prediction modeling - Part V: A practical approach to regression problems -- Supervised and unsupervised learning / clustering -- Introduction to Bayesian Modeling -- Introduction to Deep Learning -- Overview of algorithms for machine-learning based clinical prediction modelling -- Foundations of feature selection in clinical prediction modelling -- Dimensionality reduction: Foundations and applications in clinical neuroscience -- Machine learning-based survival modeling: Foundations and Applications -- Making clinical prediction models available: A brief introduction -- Machine Learning-based Clustering Analysis: Foundational Concepts, Methods, and Applications -- Introduction to Machine Learning in Neuroimaging -- Overview of machine learning algorithms in imaging -- Foundations of classification modeling based on neuroimaging -- Foundations of lesion-symptom mapping using machine learning -- Foundations of Machine Learning-Based Segmentation in Cranial Imaging -- Foundations of lesion detection using machine learning in clinical neuroimaging -- Foundations of multiparametric brain tumor imaging characterization -- Radiomics in clinical neuroscience – Overview -- Radiomic feature extraction: Methodological Foundations -- Complexity and interpretability in machine vision -- Foundations of intraoperative anatomical recognition using machine vision -- Machine Vision Foundations -- Natural Language Processing: Foundations and Applications in Clinical Neuroscience -- Foundations of Time Series Analysis -- Overview of algorithms for natural language processing and time series analysis -- History of machine learning in neurosurgery -- The AI doctor - considerations for AI-based medicine -- Ethics of Machine Learning-Based Predictive Analytics -- Predictive analytics in clinical practice: Pro and contra -- Review of machine vision applications in neuroophtalmology -- Prediction Model -- Prediction Model -- Prediction Model -- Topical Review of machine learning in intracranial aneurysm surgery -- Review of applications of machine learning in neuroimaging -- Prediction Model -- An overview of machine learning applications in the Neurointensive Care Unit -- Prediction Model -- Review of natural language processing in the clinical neurosciences -- Review of big data applications in the clinical neurosciences -- Neurosurgery Neuroradiology Neurology Ophthalmology Staartjes, Victor E. edt Regli, Luca 1962- (DE-588)1089661908 edt Serra, Carlo edt Erscheint auch als Online-Ausgabe, eBook 978-3-030-85292-4 eBook Acta neurochirurgica supplement 134 (DE-604)BV000012719 134 |
| spellingShingle | Machine learning in clinical neuroscience foundations and applications Acta neurochirurgica supplement |
| title | Machine learning in clinical neuroscience foundations and applications |
| title_auth | Machine learning in clinical neuroscience foundations and applications |
| title_exact_search | Machine learning in clinical neuroscience foundations and applications |
| title_exact_search_txtP | Machine learning in clinical neuroscience foundations and applications |
| title_full | Machine learning in clinical neuroscience foundations and applications Victor E. Staartjes, Luca Regli, Carlo Serra, editors |
| title_fullStr | Machine learning in clinical neuroscience foundations and applications Victor E. Staartjes, Luca Regli, Carlo Serra, editors |
| title_full_unstemmed | Machine learning in clinical neuroscience foundations and applications Victor E. Staartjes, Luca Regli, Carlo Serra, editors |
| title_short | Machine learning in clinical neuroscience |
| title_sort | machine learning in clinical neuroscience foundations and applications |
| title_sub | foundations and applications |
| volume_link | (DE-604)BV000012719 |
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