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  1. 1

    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

    ISSN: 1748-670X, 1748-6718, 1748-6718
    Published: United States Hindawi 07.12.2021
    “…In this paper, we have proposed a novel methodology based on statistical features and different machine learning algorithms…”
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    Journal Article
  2. 2

    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

    ISSN: 1932-6203, 1932-6203
    Published: United States Public Library of Science 21.11.2018
    Published in PloS one (21.11.2018)
    “… 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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    Journal Article
  3. 3

    Retracted: An Improved Brain MRI Classification Methodology Based on Statistical Features and Machine Learning Algorithms by Methods in Medicine, Computational and Mathematical

    ISSN: 1748-670X, 1748-6718, 1748-6718
    Published: United States Hindawi 2023
    “…[This retracts the article DOI: 10.1155/2021/8608305.]…”
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    Journal Article
  4. 4

    Efficient feature extraction methodologies for unknown MP4-Malware detection using Machine learning algorithms by Tsafrir, Tal, Cohen, Aviad, Nir, Etay, Nissim, Nir

    ISSN: 0957-4174, 1873-6793
    Published: Elsevier Ltd 01.06.2023
    Published in Expert systems with applications (01.06.2023)
    “…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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    Journal Article
  5. 5

    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

    ISSN: 2575-7288
    Published: IEEE 17.03.2023
    “… 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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    Conference Proceeding
  6. 6

    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

    ISSN: 2352-8648, 2352-8648
    Published: Elsevier B.V 01.02.2023
    Published in Digital communications and networks (01.02.2023)
    “… 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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    Journal Article
  7. 7

    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

    ISSN: 2192-6670, 2192-6662, 2192-6670
    Published: Vienna Springer Vienna 19.12.2024
    “… 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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    Journal Article
  8. 8

    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

    ISSN: 1932-6203, 1932-6203
    Published: Public Library of Science 21.11.2018
    Published in PloS one (21.11.2018)
    “… 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…”
    Get full text
    Journal Article
  9. 9

    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

    ISSN: 1932-6203, 1932-6203
    Published: Public Library of Science 21.11.2018
    Published in PloS one (21.11.2018)
    “… 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…”
    Get full text
    Journal Article
  10. 10
  11. 11

    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

    ISSN: 0360-5442
    Published: Elsevier Ltd 15.06.2015
    Published in Energy (Oxford) (15.06.2015)
    “… This research compares the accuracy of different Machine Learning methodologies for the hourly energy forecasting in buildings…”
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    Journal Article Publication
  12. 12

    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

    ISSN: 1064-7570, 1573-7705
    Published: New York Springer US 01.03.2024
    Published in Journal of network and systems management (01.03.2024)
    “… 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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    Journal Article
  13. 13

    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

    ISSN: 1932-6203, 1932-6203
    Published: United States Public Library of Science 09.04.2019
    Published in PloS one (09.04.2019)
    “…[This corrects the article DOI: 10.1371/journal.pone.0207749.]…”
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    Journal Article
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  17. 17

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

    ISSN: 2193-567X, 1319-8025, 2191-4281
    Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2022
    “… The proposed system uses a hybrid methodology for selecting features by applying feature selection methods on machine learning classifiers…”
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    Journal Article
  18. 18

    Machine learning ensemble modelling to classify caesarean section and vaginal delivery types using Cardiotocography traces by Fergus, Paul, Selvaraj, Malarvizhi, Chalmers, Carl

    ISSN: 0010-4825, 1879-0534, 1879-0534
    Published: United States Elsevier Ltd 01.02.2018
    Published in Computers in biology and medicine (01.02.2018)
    “… 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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    Journal Article
  19. 19

    Late feature fusion using neural network with voting classifier for Parkinson’s disease detection by Aljohani, Abeer

    ISSN: 1472-6947, 1472-6947
    Published: London BioMed Central 27.09.2024
    “… For the purpose of classifying Parkinson’s disease, this study suggests merging deep with machine learning recognition approaches…”
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    Journal Article
  20. 20

    Distributed Machine Learning Algorithms to classify Protein secondary structures for Drug Design-A Survey by DencelinX, Leo, Ramkumar, T

    ISSN: 0974-3618, 0974-360X, 0974-306X
    Published: Raipur A&V Publications 01.09.2017
    “… [...]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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    Journal Article