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Machine learning in clinical neuroscience :foundations and applications /
紀錄類型 ： 書目-語言資料,印刷品: 單行本
其他作者 ： Staartjes, Victor E.,
出版項 ： Cham, Switzerland :Springer,[2022]
面頁冊數 ： 1 online resource (VII, 361 pages . 133 illustrations, 80 illustrations in color.)
內容註 ： 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 -- Radiomic features associated with extent of resection in glioma surgery.
標題 ： Neurosciences - Data processing. -
標題 ： Machine learning. -
標題 ： Artificial intelligence - Medical applications. -
標題 ： Machine Learning -
ISBN ： 9783030852924
ISBN ： 303085292X
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505 0 $aPreface -- 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 -- Radiomic features associated with extent of resection in glioma surgery.
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Machine learning in clinical neuroscience :foundations and applications /Victor E. Staartjes, Luca Regli, Carlo Serra, editors. - 1 online resource (VII, 361 pages . 133 illustrations, 80 illustrations in color.) - Acta Neurochirurgica Supplement,1342197-8395 ;. - 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 -- Radiomic features associated with extent of resection in glioma surgery.
Electronic reproduction.
Ipswich, MA
Available via World Wide Web.
ISBN: 9783030852924
Standard No.: 10.1007/978-3-030-85292-4doiSubjects--Topical Terms:
101147
Neurosciences
--Data processing.
LC Class. No.: QP357.5 / .M33 2022
Dewey Class. No.: 612.80285/631
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 -- Radiomic features associated with extent of resection in glioma surgery.
Electronic reproduction.
Ipswich, MA
Available via World Wide Web.
ISBN: 9783030852924
Standard No.: 10.1007/978-3-030-85292-4doiSubjects--Topical Terms:
101147
Neurosciences
--Data processing.
LC Class. No.: QP357.5 / .M33 2022
Dewey Class. No.: 612.80285/631
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