3,327 results for machine learning
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Machine learning based approaches for detecting COVID-19 using clinical text data
…clinical reports into four classes by using classical and ensemble machine learning algorithms. Feature engineering was performed using techniques like Term frequency/inverse document frequency (TF/IDF), Bag of words (BOW) and report length. These features were supplied to traditional and ensemble…
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Water quality prediction using machine learning models based on grid search method
…optimization and tuning are utilized to improve the accuracy of several machine learning models, where the machine learning techniques are utilized for the process of predicting WQI and WQC. Grid search is a vital method used for optimizing and tuning the parameters for four classification models…
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Machine learning for brain age prediction: Introduction to methods and clinical applications
The rise of machine learning has unlocked new ways of analysing structural neuroimaging data, including brain age prediction. In this state-of-the-art review, we provide an introduction to the methods and potential clinical applications of brain age prediction. Studies on brain age typically…
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Machine learning applications in microbial ecology, human microbiome studies, and environmental monitoring
…functional diversity are key to better understanding microbial ecology. Machine learning has proven to be a useful approach for analyzing microbial community data and making predictions about outcomes including human and environmental health. Machine learning applied to microbial community profiles…
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Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction
…report, to our knowledge, the first observational cohort study to develop machine learning models for the ECG diagnosis of OMI. Using 7,313 consecutive patients from multiple clinical sites, we derived and externally validated an intelligent model that outperformed practicing clinicians and other…
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Performance Comparison and Current Challenges of Using Machine Learning Techniques in Cybersecurity
…The objective of this survey is to bestow a brief review of different machine learning (ML) techniques to get to the bottom of all the developments made in detection methods for potential cybersecurity risks. These cybersecurity risk detection methods mainly comprise of fraud detection, intrusion…
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Air pollution prediction with machine learning: a case study of Indian cities
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Comparing Different Resampling Methods in Predicting Students’ Performance Using Machine Learning Techniques
…methods better in solving the imbalanced problem, this paper uses various machine learning classifiers including Random Forest, K-Nearest-Neighbor, Artificial Neural Network, XG-boost, Support Vector Machine (Radial Basis Function), Decision Tree, Logistic Regression, and Naïve Bayes. Furthermore…
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An artificial intelligence model for heart disease detection using machine learning algorithms
The paper focuses on the construction of an artificial intelligence-based heart disease detection system using machine learning algorithms. We show how machine learning can help predict whether a person will develop heart disease. In this paper, a python-based application is developed for…
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Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction
…(NB), Decision Tree (DT), and Multivariate Logistic Regression (MLP) machine learning methods for the prediction and mapping fire susceptibility across the Pu Mat National Park, Nghe An Province, Vietnam. The modeling methodology was formulated based on processing the information from the 57…
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Machine Learning and Artificial Intelligence in Pharmaceutical Research and Development: a Review
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A Review of Machine Learning Approaches to Power System Security and Stability
…been a priority to energy stakeholders over the years. In recent times, machine learning techniques (MLTs) have proven to be effective in numerous applications including power system studies. In the literature, various MLTs such as artificial neural networks (ANN), Decision Tree (DT), support…
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RETRACTED ARTICLE: Artificial intelligence and machine learning in precision and genomic medicine
…of a broad range of datasets and modern computer techniques such as machine learning. This review article has elucidated the contributions of ML algorithms in precision and genome medicine.
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Silhouette Analysis for Performance Evaluation in Machine Learning with Applications to Clustering
Grouping the objects based on their similarities is an important common task in machine learning applications. Many clustering methods have been developed, among them k-means based clustering methods have been broadly used and several extensions have been developed to improve the original k-means…
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Evaluating urban flood risk using hybrid method of TOPSIS and machine learning
…paper, we evaluate flood riskin Jiroft city, Iran, using a combination of machine learning and decision-making methods. Flood hazard maps were created using three state-of-the-art machine learning methods (support vector machine, random forest, and boosted regression tree). The metadata supporting…
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Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain
In recent years, machine learning algorithms, and more specifically deep learning algorithms, have been widely used in many fields, including cyber security. However, machine learning systems are vulnerable to adversarial attacks, and this limits the application of machine learning, especially in…
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Machine Learning Based Indoor Localization Using Wi-Fi RSSI Fingerprints: An Overview
…In recent years, many researchers have proposed a wide range of machine learning (ML)-based indoor localization approaches using Wi-Fi received signal strength indicator (RSSI) fingerprints. This survey attempts to provide a summarized investigation of ML-based Wi-Fi RSSI fingerprinting schemes…
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LIT-PCBA: An Unbiased Data Set for Machine Learning and Virtual Screening
…novel data set (LIT-PCBA) specifically designed for virtual screening and machine learning. LIT-PCBA relies on 149 dose-response PubChem bioassays that were additionally processed to remove false positives and assay artifacts and keep active and inactive compounds within similar molecular property…
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