3.327 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
Machine learning methods for modelling the gasification and pyrolysis of biomass and waste
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Artikel Jurnal Teks lengkap
A predictive analytics approach for stroke prediction using machine learning and neural networks
The negative impact of stroke in society has led to concerted efforts to improve the management and diagnosis of stroke. With an increased synergy between technology and medical diagnosis, caregivers create opportunities for better patient management by systematically mining and archiving the…
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Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective
…years of research in computational diagnosis of diabetes have pointed to machine learning to as a viable solution for the prediction of diabetes. However, the accuracy rate to date suggests that there is still much room for improvement. In this paper, we are proposing a machine learning framework…
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Advances in machine learning and IoT for water quality monitoring: A comprehensive review
…facilitating efficient monitoring of water quality (WQ). By employing Machine learning (ML) techniques, this gathered data can be analyzed to make accurate predictions regarding water quality. These predictive insights play a crucial role in decision-making processes aimed at safeguarding water…
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Skin lesion classification of dermoscopic images using machine learning and convolutional neural network
…in the proposed work. We have analyzed the classification accuracy of the Machine Learning algorithms and Convolutional Neural Network models. We have concluded that Convolutional Neural Network provides better accuracy compared to other machine learning algorithms implemented in the proposed work…
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Identification of Risk Factors Associated with Obesity and Overweight—A Machine Learning Overview
…not to present a risk prediction model but to provide a review of various machine learning (ML) methods and their execution using available sample health data in a public repository related to lifestyle diseases, such as obesity, CVDs, and diabetes type II. In this study, we targeted people, both…
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Artikel Jurnal Teks lengkap
Machine learning and clinical epigenetics: a review of challenges for diagnosis and classification
BACKGROUND: Machine learning is a sub-field of artificial intelligence, which utilises large data sets to make predictions for future events. Although most algorithms used in machine learning were developed as far back as the 1950s, the advent of big data in combination with dramatically increased…
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Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial
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Artikel Jurnal Teks lengkap
Systematic mapping of global research on climate and health: a machine learning review
…using traditional systematic evidence mapping approaches. We aimed to use machine learning methods to systematically synthesise an evidence base on climate change and human health. METHODS: We used supervised machine learning and other natural language processing methods (topic modelling and…
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Artikel Jurnal Teks lengkap
How machine-learning recommendations influence clinician treatment selections: the example of antidepressant selection
Decision support systems embodying machine learning models offer the promise of an improved standard of care for major depressive disorder, but little is known about how clinicians' treatment decisions will be influenced by machine learning recommendations and explanations. We used a within-subject…
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Artikel Jurnal
Application of machine learning algorithms in municipal solid waste management: A mini review
…researchers have sought to use advanced technology to solve this problem. Machine learning (ML) algorithms are good at modeling complex nonlinear processes and have been gradually adopted to promote municipal solid waste management (MSWM) and help the sustainable development of the environment in…
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Machine Learning for Wireless Sensor Networks Security: An Overview of Challenges and Issues
…between sensors and the ever-changing network topology. Therefore, machine learning algorithms are one of the proposed solutions for providing security services in this type of network by including monitoring and decision intelligence. Machine learning algorithms present additional hurdles in terms…
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Artikel Jurnal Teks lengkap
A machine learning framework to improve effluent quality control in wastewater treatment plants
…of the effluent, especially when operational cost is a major concern. Machine Learning (ML) methods have therefore been used to model WWTP processes in order to avoid various shortcomings of conventional mechanistic models. However, to the best of the authors' knowledge, no ML applications have…
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Artikel Jurnal Teks lengkap
Realizing an Efficient IoMT-Assisted Patient Diet Recommendation System Through Machine Learning Model
…rationale of recommender system. This paper proposes a deep learning solution for health base medical dataset that automatically detects which food should be given to which patient base on the disease and other features like age, gender, weight, calories, protein, fat, sodium, fiber, cholesterol…
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Artikel Jurnal
A comprehensive review on detection of plant disease using machine learning and deep learning approaches
…and handled by means of applying plant disease detection approaches. Machine learning techniques will be employed in the process of disease identification on plants as it mostly applies information themselves and offers fabulous techniques for detection of plant diseases. Methods based on Machine…
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Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms
…high rates of false alarm. The relevant literature presents many machines learning based approaches for credit card detection, such as Extreme Learning Method, Decision Tree, Random Forest, Support Vector Machine, Logistic Regression and XG Boost. However, due to low accuracy, there is still a need…
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Has the Future Started? The Current Growth of Artificial Intelligence, Machine Learning, and Deep Learning
In the modern era, many terms related to artificial intelligence, machine learning, and deep learning are widely used in domains such as business, healthcare, industries, and military. In these fields, the accurate prediction and analysis of data are crucial, regardless of how large the data are…
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Artikel Jurnal Teks lengkap
Forecasting Renewable Energy Generation with Machine Learning and Deep Learning: Current Advances and Future Prospects
This article presents a review of current advances and prospects in the field of forecasting renewable energy generation using machine learning (ML) and deep learning (DL) techniques. With the increasing penetration of renewable energy sources (RES) into the electricity grid, accurate forecasting…
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Artikel Jurnal Teks lengkap
MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques
…identify and classify brain tumors. Herein, we proposed two deep learning methods and several machine learning approaches for diagnosing three types of tumor, i.e., glioma, meningioma, and pituitary gland tumors, as well as healthy brains without tumors, using magnetic resonance brain images to…
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