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Showing 1 - 20 results of 190 for search '((( fast OR face) research random three algorithm ) OR ( pain research random tree algorithm ))', query time: 0.30s Refine Results
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    Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives by Marco Cascella, Daniela Schiavo, Arturo Cuomo, Alessandro Ottaiano, Francesco Perri, Renato Patrone, Sara Migliarelli, Elena Giovanna Bignami, Alessandro Vittori, Francesco Cutugno

    Published 2023-01-01
    “…Concerning methods, early studies were conducted by machine learning algorithms such as support vector machine, decision tree, and random forest classifiers. …”
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    Predicting diabetes using supervised machine learning algorithms on E-health records by Sulaiman Afolabi, Nurudeen Ajadi, Afeez Jimoh, Ibrahim Adenekan

    Published 2025-03-01
    “…Methods: This study investigates the early detection and management of diabetes by applying machine learning techniques to electronic health records. The research explores the effectiveness of three supervised machine learning algorithms: logistic regression, Random Forest, and k-nearest neighbors (KNN), in developing predictive models for diabetes. …”
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    The impact of rainfall and slope on hillslope runoff and erosion depending on machine learning by Naichang Zhang, Zhaohui Xia, Peng Li, Qitao Chen, Ganggang Ke, Fan Yue, Fan Yue, Yaotao Xu, Tian Wang

    Published 2025-04-01
    “…To address this gap, this study, based on machine learning methods, explores the effects of rainfall type, rainfall amount, maximum 30-min rainfall intensity (I30), and slope on hillslope runoff depth (H) and erosion-induced sediment yield (S), and unveils the interactions among these factors.MethodsThe K-means clustering algorithm was used to classify 43 rainfall events into three types: A-type, B-type, and C-type. …”
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    Prediction of Corona-Virus Using Deep Learning by Laith Al-Ali

    Published 2022-12-01
    “…Artificial intelligence provides many tools for data analysis, statistical analysis, and intelligent research. In this paper, we focus on predicting COVID-19 infection, using Artificial Neural Networks (ANN), random forests and decision trees, to effectively analyze medical datasets, based on the most common and acute symptoms, such as cough, fever, headache, diarrhea, living in infected areas Pain and shortness of breath. …”
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