標題: Titlebook: Machine Learning in Clinical Neuroscience; Foundations and Appl Victor E. Staartjes,Luca Regli,Carlo Serra Conference proceedings 2022 The [打印本頁] 作者: Interjection 時間: 2025-3-21 16:56
書目名稱Machine Learning in Clinical Neuroscience影響因子(影響力)
書目名稱Machine Learning in Clinical Neuroscience影響因子(影響力)學科排名
書目名稱Machine Learning in Clinical Neuroscience網(wǎng)絡(luò)公開度
書目名稱Machine Learning in Clinical Neuroscience網(wǎng)絡(luò)公開度學科排名
書目名稱Machine Learning in Clinical Neuroscience被引頻次
書目名稱Machine Learning in Clinical Neuroscience被引頻次學科排名
書目名稱Machine Learning in Clinical Neuroscience年度引用
書目名稱Machine Learning in Clinical Neuroscience年度引用學科排名
書目名稱Machine Learning in Clinical Neuroscience讀者反饋
書目名稱Machine Learning in Clinical Neuroscience讀者反饋學科排名
作者: 勉勵 時間: 2025-3-21 21:55 作者: 品嘗你的人 時間: 2025-3-22 01:19
978-3-030-85294-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 地名詞典 時間: 2025-3-22 04:40
Machine Learning in Clinical Neuroscience978-3-030-85292-4Series ISSN 0065-1419 Series E-ISSN 2197-8395 作者: 實現(xiàn) 時間: 2025-3-22 11:47
Machine Learning-Based Clustering Analysis: Foundational Concepts, Methods, and Applicationsr clusters is one the central tasks of data science. Its exploratory and descriptive nature make it one of the most underused and underappreciated methods. In the present chapter we describe its core function with applied examples, explore different approaches, and discuss meaningful applications of the approach for the practicing researcher.作者: sinoatrial-node 時間: 2025-3-22 14:51 作者: Colonoscopy 時間: 2025-3-22 20:40
Hendrik-Jan Mijderwijk,Stefan van Beek,Daan Nieboerthe overriding goal of discovering how narrative can help us to explain life. It analyzes why novelty is so hard to comprehend in the framework of Western thinking and confronts head-on the chasm betwee978-94-007-2612-3978-1-4020-9970-0Series ISSN 1875-4651 Series E-ISSN 1875-466X 作者: 低三下四之人 時間: 2025-3-23 00:16
0065-1419 includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, and978-3-030-85294-8978-3-030-85292-4Series ISSN 0065-1419 Series E-ISSN 2197-8395 作者: 低位的人或事 時間: 2025-3-23 02:26
Machine Intelligence in Clinical Neuroscience: Taming the Unchained Prometheus,act, and deal with the many uncertainties in clinical practice, algorithms cannot. Algorithms must remain tools of our own mind, tools that we should be able to master, control, and apply to our advantage in an adjunctive manner. Our hope is that this book inspires and instructs physician-scientists作者: 統(tǒng)治人類 時間: 2025-3-23 06:37
Foundations of Machine Learning-Based Clinical Prediction Modeling: Part I—Introduction and General uning, and model selection, and ending with evaluation of model discrimination and calibration as well as robust internal or external validation of the fully developed model. Methodological rigor and clarity as well as understanding of the underlying reasoning of the internal workings of a machine l作者: opalescence 時間: 2025-3-23 12:22 作者: Jacket 時間: 2025-3-23 14:35 作者: IST 時間: 2025-3-23 20:11 作者: 得體 時間: 2025-3-23 23:41 作者: 提煉 時間: 2025-3-24 06:02 作者: Observe 時間: 2025-3-24 10:07 作者: Mumble 時間: 2025-3-24 14:37 作者: 阻止 時間: 2025-3-24 18:46
Conference proceedings 2022 instructions on how to correctly develop and validate clinical prediction models. It also includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, and作者: modish 時間: 2025-3-24 20:54 作者: RAG 時間: 2025-3-25 00:27
Victor E. Staartjes,Luca Regli,Carlo Serraronments (Juhaňák & Zounek, 2016, 2019). This book can therefore be understood as a further research path for our focus, as we have focused on digital technologies only in connection to formal education in our previous studies. In this respect, this research represents not only a follow-up to our ex作者: licence 時間: 2025-3-25 03:32
ronments (Juhaňák & Zounek, 2016, 2019). This book can therefore be understood as a further research path for our focus, as we have focused on digital technologies only in connection to formal education in our previous studies. In this respect, this research represents not only a follow-up to our ex作者: cleaver 時間: 2025-3-25 10:04
Julius M. Kernbach,Victor E. StaartjesSect. ., I will introduce the account of natural kinds considered in this paper. In Sect. ., I will first present the relevant definition of genes and how they can be classified. Then, I will argue that the gene can be considered a natural kind as it satisfies the criteria for natural kindhood. Sect作者: Infusion 時間: 2025-3-25 15:04
Julius M. Kernbach,Victor E. Staartjesointing out what these limitations are, in this chapter we try to provide an alternative analysis of incommensurability between the Modern Synthesis and the Extended Evolutionary?Synthesis. We argue that there are compelling reasons to think that both frameworks are incommensurable, thereby leaving 作者: BOLUS 時間: 2025-3-25 17:39 作者: OVER 時間: 2025-3-25 23:22 作者: 顧客 時間: 2025-3-26 03:44 作者: indoctrinate 時間: 2025-3-26 05:45 作者: Cupidity 時間: 2025-3-26 11:49 作者: 挫敗 時間: 2025-3-26 15:40
Michael C. Jin,Adrian J. Rodrigues,Michael Jensen,Anand Veeravagu work done on the ground. But scholarship is slowly making progress and permits a preliminary study like ours. Given the state of the evidence, ours is a beginning step and certainly not intended to be the last word. We are certain, as generations of unflagging academics have proved, that generous r作者: 安裝 時間: 2025-3-26 19:03 作者: arbovirus 時間: 2025-3-26 21:10 作者: HARD 時間: 2025-3-27 03:48
Miquel Serra-Burriel,Christopher Ames minutia of this deterministic, machine-like, predictable world; this observatory position is a gift from our Creator. Such a framework enabled the foundation in modernity of the natural sciences and technology, and the establishment of the metaphysical worldview we inhabit today. Science later simp作者: 有組織 時間: 2025-3-27 06:14
Adrian E. Jimenez,James Feghali,Andrew T. Schilling,Tej D. Azad minutia of this deterministic, machine-like, predictable world; this observatory position is a gift from our Creator. Such a framework enabled the foundation in modernity of the natural sciences and technology, and the establishment of the metaphysical worldview we inhabit today. Science later simp作者: 到婚嫁年齡 時間: 2025-3-27 13:14
Hendrik-Jan Mijderwijk,Daan Nieboer minutia of this deterministic, machine-like, predictable world; this observatory position is a gift from our Creator. Such a framework enabled the foundation in modernity of the natural sciences and technology, and the establishment of the metaphysical worldview we inhabit today. Science later simp作者: ADJ 時間: 2025-3-27 16:39
rmation about Life.? ..The information presented here on the various phenomena of Life were all written by highly qualified authors including scientists, public leaders, a professional athelete and three Nobel Laureates. .978-90-481-7121-7978-1-4020-4403-8Series ISSN 1566-0400 Series E-ISSN 2215-0048 作者: 利用 時間: 2025-3-27 21:32
Julius M. Kernbach,Jonas Ort,Karlijn Hakvoort,Hans Clusmann,Georg Neuloh,Daniel Delevrmation about Life.? ..The information presented here on the various phenomena of Life were all written by highly qualified authors including scientists, public leaders, a professional athelete and three Nobel Laureates. .978-90-481-7121-7978-1-4020-4403-8Series ISSN 1566-0400 Series E-ISSN 2215-0048 作者: Overdose 時間: 2025-3-27 23:32 作者: meretricious 時間: 2025-3-28 03:08
Machine Intelligence in Clinical Neuroscience: Taming the Unchained Prometheus,a, increasing computing power even on mobile devices, and online training resources have both led to an explosion in applications and publications of ML in the clinical neurosciences, but has also enabled a dangerous amount of flawed analyses and cardinal methodological errors committed by benevolen作者: 和平 時間: 2025-3-28 09:31
Foundations of Machine Learning-Based Clinical Prediction Modeling: Part I—Introduction and General ictive modeling, which is the focus of this series. In particular, we define the terms machine learning, artificial intelligence, as well as supervised and unsupervised learning, continuing by introducing optimization, thus, the minimization of an objective error function as the central dogma of mac作者: pulse-pressure 時間: 2025-3-28 12:57 作者: Commentary 時間: 2025-3-28 14:36 作者: 出血 時間: 2025-3-28 19:20 作者: LAY 時間: 2025-3-29 02:37
Foundations of Machine Learning-Based Clinical Prediction Modeling: Part V—A Practical Approach to Rme. We supply fully structured code for the readers to download and execute in parallel to this section, as well as a simulated database of 10,000 glioblastoma patients who underwent microsurgery, and predict survival from diagnosis in months. We walk the reader through each step, including import, 作者: Proponent 時間: 2025-3-29 05:59 作者: lanugo 時間: 2025-3-29 07:17 作者: 黑豹 時間: 2025-3-29 13:11
A Discussion of Machine Learning Approaches for Clinical Prediction Modeling have led to broad diversification of approaches. These range from humble regression-based models to more complex artificial neural networks; yet, despite heterogeneity in foundational principles and architecture, the spectrum of machine learning approaches to clinical prediction modeling have invar作者: 個人長篇演說 時間: 2025-3-29 16:55 作者: 向下五度才偏 時間: 2025-3-29 19:45
Introduction to Deep Learning in Clinical Neurosciencerithms, architecturally similar to neural networks of the brain. We provide examples of DL in analyzing MRI data and discuss potential applications and methodological caveats..Important aspects are ., ., and specific task-performing DL methods, such as . and .. Additionally, . and . are useful DL te作者: convert 時間: 2025-3-30 00:51
Machine Learning-Based Clustering Analysis: Foundational Concepts, Methods, and Applicationsr clusters is one the central tasks of data science. Its exploratory and descriptive nature make it one of the most underused and underappreciated methods. In the present chapter we describe its core function with applied examples, explore different approaches, and discuss meaningful applications of作者: Eosinophils 時間: 2025-3-30 05:19 作者: Abduct 時間: 2025-3-30 08:55
Updating Clinical Prediction Models: An Illustrative Case Study poorly at external validation. Model updating is an efficient technique and promising alternative to the de novo development of clinical prediction models. Model updating has been recommended by the TRIPOD guidelines. To illustrate several model updating techniques, a case study is provided for the作者: SLAG 時間: 2025-3-30 14:44 作者: 原諒 時間: 2025-3-30 18:36 作者: Rheumatologist 時間: 2025-3-31 00:25 作者: FLIRT 時間: 2025-3-31 00:59
their time in this environment, where they encounter digital technologies in various situations and contexts. In the family environment, generations meet that grew up in different times and have diverse experiences with digital technologies. The parents usually represent a generation that grew up wh作者: 水獺 時間: 2025-3-31 08:05
Victor E. Staartjes,Luca Regli,Carlo Serrarimarily on the results of a research project conducted over several years in which this topic was the central focus. We introduce the research design and project methodology in more detail in this chapter. In the course of writing of this book, we also built on our previous studies concerning digit
