Showing 1 - 20 results of 97 for search '(( data boosting algorithm ) OR ((( element scheduling algorithm ) OR ( patient data algorithm ))))', query time: 0.12s Refine Results
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    Boosting the visibility of services in microservice architecture by Ahmet Vedat Tokmak (17773479)

    Published 2023
    “…Our research also analyzed the boosting algorithms, namely Gradient Boost, XGBoost, LightGBM, and CatBoost to improve the overall performance. …”
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    The Relation Between Respiratory & Acute Coronary Syndrome Using Data Mining Techniques by DOULEH, HANI ABDULLAH YOSEF ABU

    Published 2018
    “…In this study I’ve split one dataset of patients who have attended to emergency departments in Abu Dhabi hospitals to two datasets (Respiratory and Cardiac), then applied the data mining algorithms on each dataset and one time on the original dataset. …”
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    GENETIC SCHEDULING OF TASK GRAPHS by Benten, M. S.

    Published 2020
    “…A genetic algorithm for scheduling computational task graphs is presented. …”
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    article
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    A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

    Published 2019
    “…The reported accuracy dramatically outperforms the previous algorithms, including gradient tree boosting (GTB), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and linear discriminant analysis (LDA). …”
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    An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems by Boukhari, Bahia

    Published 2019
    “…The healthcare systems storing highly sensitive information can be targeted by attackers aiming to insert, delete, or modify the data stored. These malicious activities may cause serious harm to the database accessibility and lead to catastrophic long-term harm to the patients' health. …”
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    masterThesis
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    Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

    Published 2019
    “…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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    Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

    Published 2023
    “…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”
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    Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk by Mohamed Chaouch (17983846)

    Published 2025
    “…Additionally, an online classifier is developed for streaming data, combining online PCA with a kernel-based recursive classifier using a stochastic approximation algorithm. …”
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    Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

    Published 2024
    “…For such high-dimension data our approach outperforms the Synthetic Minority Oversampling Technique for Regression (SMOTER) algorithm for the IMDB-WIKI and AgeDB image datasets. …”
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    Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper by Mutaz I. Othman (21186827)

    Published 2025
    “…Future research should focus on refining algorithms, ensuring real‐time adaptability, addressing ethical considerations, evaluating long‐term patient outcomes, fostering cooperative systems, and integrating relevant data and policies within the healthcare framework.…”