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An Improved Brain MRI Classification Methodology Based on Statistical Features and Machine Learning Algorithms by Fayaz, Muhammad, Qureshi, Muhammad Shuaib, Kussainova, Karlygash, Burkanova, Bermet, Aljarbouh, Ayman, Qureshi, Muhammad Bilal

“…In this paper, we have proposed a novel methodology based on statistical features and different machine learning algorithms…”
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Machine learning model combining features from algorithms with different analytical methodologies to detect laboratory-event-related adverse drug reaction signals by Jeong, Eugene, Park, Namgi, Choi, Young, Park, Rae Woong, Yoon, Dukyong

“… In this study, we propose a machine learning (ML) model that enables accurate ADR signal detection by integrating features from existing algorithms based on inpatient EHR laboratory results…”
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Retracted: An Improved Brain MRI Classification Methodology Based on Statistical Features and Machine Learning Algorithms by Methods in Medicine, Computational and Mathematical

“…[This retracts the article DOI: 10.1155/2021/8608305.]…”
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Evaluation of Machine Learning Algorithms on Finding Drinking Water Quality Based on Feature Selection Methodologies by Priya, K. Devi, Sai, Sanga Monish, Pagadala, Venu Gopal Reddy, Kumar, Dasari Praveen

“… Here, analyzed the factors that decide the quality of the water using 11 AI based classifiers with feature selection techniques and evaluated performance metrics…”
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Efficient feature extraction methodologies for unknown MP4-Malware detection using Machine learning algorithms by Tsafrir, Tal, Cohen, Aviad, Nir, Etay, Nissim, Nir

“…We are living in an era in which daily interaction between individuals and businesses involves sending, uploading, and sharing videos as a means of…”
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Internet of things intrusion detection model and algorithm based on cloud computing and multi-feature extraction extreme learning machine by Lin, Haifeng, Xue, Qilin, Feng, Jiayin, Bai, Di

“… In view of this situation, this study applies cloud computing and machine learning to the intrusion detection system of IoT to improve detection performance…”
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Detection of ovarian cancer using a methodology with feature extraction and selection with genetic algorithms and machine learning by Acosta-Jiménez, Samara, Mendoza-Mendoza, Miguel M., Galván-Tejada, Carlos E., Galván-Tejada, Jorge I., Celaya-Padilla, José M., García-Domínguez, Antonio, Gamboa-Rosales, Hamurabi, Solís-Robles, Roberto

“… This study presents a method to predict ovarian cancer by combining machine learning and feature selection using the genetic algorithm GALGO…”
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Hybrid methodologies for electricity load forecasting: Entropy-based feature selection with machine learning and soft computing techniques by Jurado, Sergio, Nebot, Àngela, Mugica, Fransisco, Avellana, Narcís

“… This research compares the accuracy of different Machine Learning methodologies for the hourly energy forecasting in buildings…”
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Correction: Machine learning model combining features from algorithms with different analytical methodologies to detect laboratory-event-related adverse drug reaction signals by Jeong, Eugene, Park, Namgi, Choi, Young, Park, Rae Woong, Yoon, Dukyong

“…[This corrects the article DOI: 10.1371/journal.pone.0207749.]…”
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Unsupervised Clustering for a Comparative Methodology of Machine Learning Models to Detect Domain-Generated Algorithms Based on an Alphanumeric Features Analysis by Hassaoui, Mohamed, Hanini, Mohamed, El Kafhali, Said

“… This article proposes a comparative methodology to compare machine learning models based on unsupervised clustering and then applied this methodology to study the best…”
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Retracted: Traditional Ceramic Sculpture Feature Recognition Based on the Machine Learning Algorithm by Mobile Computing, Wireless Communications and

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Analysis of Machine Learning Classifiers for Early Detection of DDoS Attacks on IoT Devices by Gaur, Vimal, Kumar, Rajneesh

“… The proposed system uses a hybrid methodology for selecting features by applying feature selection methods on machine learning classifiers…”
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Machine learning ensemble modelling to classify caesarean section and vaginal delivery types using Cardiotocography traces by Fergus, Paul, Selvaraj, Malarvizhi, Chalmers, Carl

“… This study presents a review of human Cardiotocography trace interpretation and argues that machine learning, used as a decision support system by obstetricians and midwives, may provide an objective…”
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Late feature fusion using neural network with voting classifier for Parkinson’s disease detection by Aljohani, Abeer

“… For the purpose of classifying Parkinson’s disease, this study suggests merging deep with machine learning recognition approaches…”
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Distributed Machine Learning Algorithms to classify Protein secondary structures for Drug Design-A Survey by DencelinX, Leo, Ramkumar, T

“… [...]this review is divided into three main sections, First section explains about the properties of amino acids which aids in identifying the secondary structure and the various features used…”
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Enhancing Postpartum Haemorrhage Prediction Through the Integration of Classical Logistic Regression and Machine Learning Algorithms by Lérias-Cambeiro, Muriel, Mugeiro-Silva, Raquel, Rodrigues, Anabela, Dias-Domingues, Tiago, Lança, Filipa, Vaz Carneiro, António

“… outcomes.This study aims to evaluate various exploratory and classification methodologies, alongside optimisation strategies, for identifying predictors of postpartum haemorrhage…”
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Load Disaggregation Using Microscopic Power Features and Pattern Recognition by de Souza, Wesley Angelino, Garcia, Fernando Deluno, Marafão, Fernando Pinhabel, da Silva, Luiz Carlos Pereira, Simões, Marcelo Godoy

“… Initially, the novel NILM algorithm—called the Power Signature Blob (PSB)—makes use of a state machine to detect when the appliance has been turned on or off…”
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Bridging Neuroscience and Machine Learning: A Gender-Based Electroencephalogram Framework for Guilt Emotion Identification by Zaidi, Saima Raza, Khan, Najeed Ahmed, Hasan, Muhammad Abul

“… In the pre-processing step, collected data were de-noised using bandpass filters and ICA, then segmented into smaller sections for further analysis…”
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3D Reconstruction based on multi-view stereo in the deep learning era: a survey and comparison of methods by Song, Boyang, Wu, Bing, Xiao, Jin, Hu, Xiaoguang, Shi, Jiaqi, Zhang, Baochang

“…This paper provides an in-depth review of deep learning methodologies to address Multi-view Stereo (MVS) challenges…”
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Analysis of data-driven approaches for radar target classification by Coşkun, Aysu, Bilicz, Sándor

“… Design/methodology/approach The approach involves several supervised machine learning and classification methods, including traditional algorithms and a deep neural network classifier…”
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