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model implementation » broader implementation (Expand Search), system implementation (Expand Search), _ implementation (Expand Search)
code » mode (Expand Search), core (Expand Search)
predicted » predict (Expand Search)
model implementation » broader implementation (Expand Search), system implementation (Expand Search), _ implementation (Expand Search)
code » mode (Expand Search), core (Expand Search)
predicted » predict (Expand Search)
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1
Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic
Published 2025“…</p><h3>Conclusion</h3><p dir="ltr">This study indicated that predictive modelling could accurately help identify patients who refuse transport to hospital and may not require treatment on the scene. …”
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Hybrid Model for Detection of Cervical Cancer Using Causal Analysis and Machine Learning Techniques
Published 2022“…This research work analyses cervical cancer and various risk factors to help detect cervical cancer. The proposed model Boruta with SVM and various popular ML models are implemented using Python and various performance measuring parameters, i.e., accuracy, precision, F 1 – Score , and recall. …”
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3
A study on Speaker Recognition System
Published 2015“…The proposed system was mainly developed using Python (Python.org, 2015). This system was used to implement and study several methods and techniques in speaker recognition domain. …”
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4
Arabic Educational Neural Network Chatbot
Published 2023“…Finally, we programmed the chabot and the models in Python. As a consequence, an Arabic chatbot answers all questions about educational regulations in the United Arab Emirates.…”
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5
Investigation of Forming a Framework to shortlist contractors in the tendering phase
Published 2022“…After obtaining the weights of the decision factors, a model using Machine Learning algorithm on Google Colab was written using the Python language. …”
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6
KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”