204,674 results for machine learning
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Journal Article
Harnessing machine learning in contemporary tobacco research
Machine learning (ML) has the potential to transform tobacco research and address the urgent public health crisis posed by tobacco use. Despite the well-documented health risks, cessation rates remain low. ML techniques offer innovative solutions by analyzing vast datasets to uncover patterns in…
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Journal Article
Machine Learning for Chemistry: Basics and Applications
The past decade has seen a sharp increase in machine learning (ML) applications in scientific research. This review introduces the basic constituents of ML, including databases, features, and algorithms, and highlights a few important achievements in chemistry that have been aided by ML techniques…
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Journal Article
Application of machine learning for coastal flooding
…damage. This necessitates a review to provide an appraisal of how machine learning can be used for coastal flooding management. The study considered articles published between 2000 and 2025 from academic databases. A systematic literature assessment was carried out based on Preferred Reporting…
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Journal Article Full text
Machine Learning Algorithm to Detect Neurological Disorder
…of such disorders. The diagnosis is accomplished by implementing machine learning techniques which aid in proper treatment. In this paper signals are acquired using electroencephalogram, a technique, that consists of parameters to classify different neurological disorders such as anxiety, epilepsy…
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Journal Article
Machine Learning- Based Optimization Of Cytotoxicity Testing
Aim or purpose: This study utilizes machine learning to enhance the cytotoxicity testing of pure zinc. It explores the potential for standardizing such tests across degradable metals and predict the refinement of standard procedures for related in vitro experiments. Materials and methods: Data from…
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Terrorist Prediction Algorithm Based on Machine Learning
…against them,so as to reduce the loss of people and property.Therefore,machine learning methods are used to predict one or more suspects based on the multiple characteristics of terrorist attacks.Bayesian optimization is used to optimize four algorithms,including Bagging,decision tree,random forest…
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Journal Article Full text
Machine Learning Methods in Investor Risk Profiling
…questionnaire responses. The users' actions are then classified using machine learning methods. As a result, it was shown that the constructed model correctly predicts 65.78 % of investors’ decisions, whereas the survey correctly identified the risk profile of only 53.7 % of investors. These…
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Journal Article
Prediction of Breast Cancer Using Machine Learning
…object of this study is to predict the breast cancer risk using various machine-learning approaches based on demographic, laboratory, and mammographic data. It employed a quantitative research design to assess the potential of machine learning (ML) in predicting breast cancer. It integrated…
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Journal Article Full text
Email classification analysis using machine learning techniques
…contribute to solving this problem by a focus on advanced machine learning algorithms and improved models for detecting spam emails but there is still a gap in features. To achieve good results, features also play an important role. To evaluate the performance of applied classifiers, 10-fold…
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Journal Article
Evaluating Cervical Cancer Risk Using Machine Learning
…datasets. Therefore, this study aimed to evaluate the effectiveness of machine learning (ML) models applied to the University of California, Irvine (UCI), cervical cancer risk factors dataset in predicting cervical health outcomes and supporting early detection strategies. Methods: This study was…
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Journal Article
Application of machine learning in personalized medicine
With the deepening of machine learning research in the medical field. At present, more and more studies have applied it to individualized medicine such as drug concentration monitoring and adverse reaction prediction. Compared with traditional population pharmacokinetic modeling methods, machine…
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Journal Article
Loan Default Prediction Using Machine Learning Algorithms
…losses. The objective of this study is to identify the most suitable machine learning model to predict loan default by comparing four models which are Random Forest, Decision Tree, Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM). Additionally, it also examines…
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Journal Article
Koina: Democratizing machine learning for proteomics research
Abstract Recent developments in machine learning (ML) and deep learning have immense potential for applications in proteomics, such as generating spectral libraries, improving peptide identification, and optimizing targeted acquisition modes. Although new ML models are regularly published, the rate…
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Journal Article Full text
Advances in Cancer Through Machine Learning Models
The integration of machine learning (ML) algorithms in oncology creates a new path for prognosis, early diagnosis, prevention, and treatment customization. However, large-scale clinical implementation is difficult due to the lack of standardized assessments and the variation in reported…
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Journal Article
Optimal invariant sets for atomistic machine learning
Abstract The representation of atomic configurations for machine learning models has led to numerous sets of descriptors. However, many descriptor sets are incomplete and/or functionally dependent. Incomplete sets cannot faithfully represent atomic environments. Yet complete constructions often…
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Journal Article
Machine learning predicts meter-scale laboratory earthquakes
Abstract 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…
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Journal Article
Machine learning approach for water quality analysis
…required. For this reason, this study investigates a number of supervised machine learning algorithms to estimate the water quality class (WQC), a unique class defined based on the WQI, and the water quality index (WQI), a singular index to describe the overall quality of water. Four input factors…
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Journal Article
Optimizing employee promotion predictions using machine learning
…frameworks. This study addresses these issues by applying advanced machine learning models to improve decision-making in human resource management. Using a dataset comprising 54 808 employee records, the study evaluates eight models, including Random Forest, Logistic Regression, SVM, AdaBoost…
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