214.423 hasil untuk machine learning
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Automation of Rietveld refinement through machine learning
Rietveld refinement is a widely used technique for determining crystal structures from powder X-ray diffraction data. Despite its broad applicability, the refinement process often requires substantial manual effort and expert knowledge, which limits the pace of materials research. Here, we…
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Using Machine Learning to Predict Early Preparation of Pharmacy Prescriptions at PSMMC - a Comparison of Four Machine Learning Algorithms
…OBJECTIVE: A healthcare framework has been constructed utilizing a machine learning approach to construct an early predicting preparation model of pharmacy prescriptions and the worthiness of changing the outpatient pharmacy workflow. METHODS: Data sets were retrieved between Januarys and June 2019…
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The NERVE-ML (neural engineering reproducibility and validity essentials for machine learning) checklist: ensuring machine learning advances neural engineering(*)
Objective. Machine learning’s (MLs) ability to capture intricate patterns makes it vital in neural engineering research. With its increasing use, ensuring the validity and reproducibility of ML methods is critical. Unfortunately, this has not always been the case in practice, as there have been…
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A Machine Learning Approach to Predicting Mortality Risk in Chemotherapy-Treated Lung Cancer: Machine Learning Model Development and Validation
…management of this population, this study developed a multivariate machine learning (ML) model to assess all-cause mortality risk in chemotherapy-treated patients with lung cancer. METHODS: This study retrospectively recruited 1278 postchemotherapy patients with lung cancer from Guangzhou Chest…
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Convex Optimization for Machine Learning
…in a widening array of practical contexts with a particular emphasis on machine learning. The first part of the book covers core concepts of convex sets, convex functions, and related basic definitions that serve understanding convex optimization and its corresponding models. The second part deals…
Juga tersedia di: DOAB
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Machine Learning in Social Science
This open access book explores how machine learning can enhance both quantitative and qualitative research in sociology. By developing algorithms tailored to specific data, machine learning enables social scientists to uncover patterns, generate new theories, calibrate indicators, and strengthen…
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Mathematical Optimization for Machine Learning
Mathematical optimization and machine learning are closely related. This proceedings volume of the Thematic Einstein Semester 2023 of the Berlin Mathematics Research Center MATH+ collects recent progress on their interplay in topics such as discrete optimization, nonlinear programming, optimal…
Juga tersedia di: DOAB
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Machine Learning for Brain Disorders
This Open Access volume provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts. Part One presents the fundamentals of ML. Part Two looks at the…
Juga tersedia di: DOAB
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Machine Learning Applications in Seismology
The purpose of this Special Issue is to immerse readers in the transformative impact of machine learning-based artificial intelligence on seismology. From digital seismic data processing to the development of structured seismic catalogs, AI technology is poised to revolutionize our understanding of…
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Entropy in Machine Learning Applications
The aim of this reprint is to inform readers of the latest developments in methods and applications of machine learning and deep learning in certain fields, including the following: a semantically enhanced social network user alignment algorithm to perform user alignment; a congestion control…
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Computational Intelligence and Machine Learning
This Special Issue presents a curated collection of ten research articles that reflect current trends and challenges in computational intelligence and machine learning. The selected works cover a broad spectrum of methods and applications, including personalized recommendation systems, social-aware…
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Applied Mathematics and Machine Learning
The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering…
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New Advances in Machine Learning
The purpose of this book is to provide an up-to-date and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call “learning” tasks, as we use the word in daily life. It is also broad enough…
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Social Media and Machine Learning
Social media has transformed society and the way people interact with each other. The volume and speed in which new content is being generated surpasses the processing capacity of machine learning systems. Analyzing such data demands new approaches coming from natural language processing, text…
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An integrated framework for applying machine learning in intelligent decision support systems
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