204.674 hasil untuk machine learning
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Artikel Jurnal
Predicting Active Antimicrobial Compounds Using Machine Learning
…this article as: Arman İ. Predicting active antimicrobial compounds using machine learning. Trends in Pharmacy 2025, 2, 0018, doi: 10.5152/TrendsPharm.2025.25018.
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Artikel Jurnal
Detecting Need-Attention Patients using Machine Learning
In healthcare, detecting patients who need immediate attention is difficult. Identifying the critical variables is challenging in patient detection because human intervention in variable selection is required. Consequently, patients who need immediate attention often experience prolonged waiting…
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Artikel Jurnal
Machine learning techniques for lipid nanoparticle formulation
…With advancements in computer science, we argue that the use of machine learning can accelerate the design of ionizable lipids systematically. Assuming researchers in lipid nanoparticle synthesis may come from various backgrounds, an entry-level guide is needed to outline and summarize the general…
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Artikel Jurnal
Forecasting Solar Energy Production Using Machine Learning
…weather patterns over time. In this paper, a hybrid model that integrates machine learning and statistical approaches is suggested for predicting future solar energy generation. In order to improve the accuracy of the suggested model, an ensemble of machine learning models was used in this study…
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Artikel Jurnal
Predicting Increased Blood Pressure Using Machine Learning
The present study investigates the prediction of increased blood pressure by body mass index (BMI), waist (WC) and hip circumference (HC), and waist hip ratio (WHR) using a machine learning technique named classification tree. Data were collected from 400 college students (56.3% women) from 16 to…
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Artikel Jurnal
Assessing smart cities' effectiveness: machine learning approaches
…and incorporating basic measures of technological development, machine-learning models were constructed using RapidMiner Studio. These models aim to predict the Human Development Index (HDI) of the city and discern the most impactful drivers related to citizens' life satisfaction. The research…
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Artikel Jurnal
Hands-On Introduction to Quantum Machine Learning
This tutorial introduces key concepts in Quantum Machine Learning (QML), covering qubits, gates, entanglement, parameterized circuits, and quantum neural networks (QNNs). It highlights recent advances in quantum-enhanced model compression and quantum architecture search (QAS), which improve QML…
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Artikel Jurnal
Elemental augmentation of machine learning interatomic potentials
Machine learning interatomic potentials (MLIPs) bridge the gap between the accuracy of ab initio methods and the computational efficiency needed for large-scale simulations. However, custom-trained MLIPs are often limited to specific materials and lack flexibility for incorporating additional…
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Artikel Jurnal
Interpretable machine learning for precision cognitive aging
…regression-based approaches. To bridge this gap, the Explainable Boosting Machine (EBM), a class of generalized additive models has been introduced, combining the strengths of interpretable and high-performing models. EBM may be particularly well-suited for cognitive health research, where…
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Artikel Jurnal
MLPro 2.0 - Online machine learning in Python
In this paper, we present version 2.0 of the open-source middleware MLPro for applied machine learning in Python. Notably, it introduces the new sub-framework MLPro-OA for online machine learning, focusing on standards and templates for classic and online-adaptive data stream processing…
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Artikel Jurnal Teks lengkap
Parkinson’s Disease Prediction System in Machine Learning
…successful treatment and management of the disease. In past few years, Machine learning (ML) algorithms has shown great potential in predicting PD based on various physiological and neurological markers. In this disease prediction system, a system is proposed using ML-based approach to predict the…
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Artikel Jurnal Teks lengkap
Face Mask Wearing Classification Using Machine Learning
…Therefore, this paper aims to analyze how image classification using machine learning algorithms can be used to detect whether a face mask is properly worn. In this research, a total of 1222 color images (selfies) were used to build five machine learning models, in particular Naïve Bayes (NB)…
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Artikel Jurnal
Predicting ward transfer mortality with machine learning
…of admission, the second set is more clinically relevant. We trained 16 machine learning models using both datasets. The best-performing models were fine-tuned and evaluated. The LightGBM model achieved the best results for both datasets. The model trained with 22 variables achieved a Receiver…
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Artikel Jurnal
ManufacturingNet: A machine learning toolbox for engineers
…To overcome these barriers, we propose ManufacturingNet, an open-source machine learning tool that enables engineers to develop complex machine learning and deep learning models with minimal programming and data science experience. We have also curated nine publicly-available datasets and…
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Artikel Jurnal
Utility-Embraced Microaggregation for Machine Learning Applications
…sense of reducing the information loss and/or computational complexity, machine learning (ML) models using the resulting aggregated data face the problem that they are not as effective as expected. Motivated by the fact that ML models can be heavily influenced by distorted training data (albeit…
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Artikel Jurnal
Classifying Interplanetary Discontinuities Using Supervised Machine Learning
…in 2008, 1,997 events are simple, and 3,197 are complex. A supervised machine learning approach is used to recognize and predict these events. Two models are trained: one for 2007, which is used to predict the results in 2008, and vice versa for 2008. To validate our results, we investigate the…
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Artikel Jurnal
Histological stain evaluation for machine learning applications
…histological stains for automatic pattern and image analysis. Background: Machine learning and image analysis are becoming increasingly important in pathology applications for automatic analysis of histological tissue samples. Pathologists rely on multiple, contrasting stains to analyze tissue…
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Artikel Jurnal Teks lengkap
Unsupervised Machine Learning to Identify Depressive Subtypes
Objectives This study evaluated an unsupervised machine learning method, latent Dirichlet allocation (LDA), as a method for identifying subtypes of depression within symptom data. Methods Data from 18,314 depressed patients were used to create LDA models. The outcomes included future emergency…
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Artikel Jurnal
Machine learning magnetism classifiers from atomic coordinates
…is still largely limited to collinear magnetism. Here, we present a machine learning model that aims to classify the magnetic structure by inputting atomic coordinates containing transition metal and rare earth elements. By building a Euclidean equivariant neural network that preserves the…
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