بدائل البحث:
guided optimization » based optimization (توسيع البحث), model optimization (توسيع البحث)
driven optimization » design optimization (توسيع البحث), dose optimization (توسيع البحث), process optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
binary wave » binary image (توسيع البحث)
guided optimization » based optimization (توسيع البحث), model optimization (توسيع البحث)
driven optimization » design optimization (توسيع البحث), dose optimization (توسيع البحث), process optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
binary wave » binary image (توسيع البحث)
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1
Models’ performance without optimization.
منشور في 2024"…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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2
Data_Sheet_1_Prediction of patient choice tendency in medical decision-making based on machine learning algorithm.pdf
منشور في 2023"…Objective<p>Machine learning (ML) algorithms, as an early branch of artificial intelligence technology, can effectively simulate human behavior by training on data from the training set. …"
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3
RNN performance comparison with/out optimization.
منشور في 2024"…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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4
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5
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6
Datasets used for the study and their sources.
منشور في 2023"…Projecting into 2030, this study aimed at providing geographical information data for guiding future policies on siting required healthcare facilities. …"
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Proposed method approach.
منشور في 2024"…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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10
LSTM model performance.
منشور في 2024"…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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11
Descriptive statistics.
منشور في 2024"…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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12
CNN-LSTM Model performance.
منشور في 2024"…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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13
MLP Model performance.
منشور في 2024"…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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14
RNN Model performance.
منشور في 2024"…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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15
CNN Model performance.
منشور في 2024"…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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16
Bi-directional LSTM Model performance.
منشور في 2024"…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …"
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Image 2_Integrative prognostic modeling for stage III lung adenosquamous carcinoma post-tumor resection: machine learning insights and web-based implementation.png
منشور في 2024"…Introduction<p>The prognostic landscape of stage III Lung Adenosquamous Carcinoma (ASC) following primary tumor resection remains underexplored. A thoughtfully developed prognostic model has the potential to guide clinicians in patient counseling and the formulation of effective therapeutic strategies.…"
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19
Image 1_Integrative prognostic modeling for stage III lung adenosquamous carcinoma post-tumor resection: machine learning insights and web-based implementation.png
منشور في 2024"…Introduction<p>The prognostic landscape of stage III Lung Adenosquamous Carcinoma (ASC) following primary tumor resection remains underexplored. A thoughtfully developed prognostic model has the potential to guide clinicians in patient counseling and the formulation of effective therapeutic strategies.…"
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20
Supplementary file 1_A study on a real-world data-based VTE risk prediction model for lymphoma patients.docx
منشور في 2025"…</p>Results<p>Combining different imputation, sampling, and feature selection strategies yielded 27 datasets, which were trained across nine algorithms to generate 243 models. The optimal model—Simp-SMOTE_rf_GBM, constructed using random forest imputation, SMOTE oversampling, and gradient boosting machine—achieved the highest predictive performance (AUC = 0.954). …"