359.866 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
Machine Learning Phase Classification of Thermoelectric Materials
In this study, we employ a Support Vector Machine (SVM) model to efficiently classify the phases of thermoelectric (TE) alloys. While ab initio calculations and experiments have explored the phases of functional TE materials, the large variety of alloys makes these explorations time-consuming and…
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Artikel Jurnal Teks lengkap
Machine learning predicts meter-scale laboratory earthquakes
In recent years, there has been a growing interest in utilizing machine learning (ML) to investigate the predictability of shear-slip failures, known as laboratory quakes, in centimeter-scale rock-friction experiments. However, the applicability of ML to larger-scale laboratory quakes and natural…
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Artikel Jurnal Teks lengkap
Machine Learning-Based Transcriptomic Diagnosis of Periodontitis
…by subjectivity and low sensitivity. This study aimed to develop a machine learning (ML)-based diagnostic framework using transcriptomic data to enhance diagnostic accuracy and efficiency. METHODS: Transcriptomic datasets from 616 samples (452 periodontitis, 164 healthy controls) were retrieved…
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Artikel Jurnal Teks lengkap
Prediction of stillbirth using machine learning methods
This study developed a machine learning model to predict stillbirth using retrospective data from 32,953 singleton pregnancies at multi-centers in South Korea. Variables were collected at baseline, E1 (before 13 weeks of pregnancy), and T0 (before 28 weeks of pregnancy). Each separate cohort (all…
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Artikel Jurnal Teks lengkap
Incisional hernia prediction using machine learning models
…low or high Risk. There is no currently full peer-reviewed study in which Machine learning (ML) is applied for the prediction of IH, so the objective of this study was to develop a predictive model of IH based on different ML techniques. METHODS: Retrospective cohort study type of diagnostic tests…
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Artikel Jurnal Teks lengkap
Unraveling sperm kinematic heterogeneity with machine learning
…for analysis using conventional statistical methods. Advances in machine learning and deep learning have addressed these limitations by leveraging motility parameters and trajectory representations for automated classification and clustering of motility patterns. These methods, including supervised…
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Artikel Jurnal Teks lengkap
Machine Learning-Assisted Quantification of Organelle Abundance
…potential bias and variability. To address this issue, we present a machine learning–assisted algorithm that allows for the quantification of organelle density using the open-source Fiji platform and WEKA segmentation. Our method enables the automated quantification of organelle number, area, and…
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Artikel Jurnal Teks lengkap
Advances in Machine Learning for Wearable Sensors
Recent years have witnessed tremendous advances in machine learning techniques for wearable sensors and bioelectronics, which play an essential role in real-time sensing data analysis to provide clinical-grade information for personalized healthcare. To this end, supervised learning and…
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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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Artikel Jurnal
Is Machine Learning Real Learning?
The question of whether machine learning is real learning is ambiguous, because the term “real learning” can be understood in two different ways. Firstly, it can be understood as learning that actually exists and is, as such, opposed to something that only appears to be learning, or is misleadingly…
Juga tersedia di: DOAJ
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Artikel Jurnal Teks lengkap
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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Artikel Jurnal Teks lengkap
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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Artikel Jurnal Teks lengkap
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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Buku Teks lengkap
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…
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Buku Teks lengkap
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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Buku Teks lengkap
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…
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