بدائل البحث:
significantly advanced » significantly enhanced (توسيع البحث), significantly enhance (توسيع البحث), significantly enhances (توسيع البحث)
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
advanced decrease » advanced disease (توسيع البحث), advanced defense (توسيع البحث), advanced breast (توسيع البحث)
significantly advanced » significantly enhanced (توسيع البحث), significantly enhance (توسيع البحث), significantly enhances (توسيع البحث)
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
advanced decrease » advanced disease (توسيع البحث), advanced defense (توسيع البحث), advanced breast (توسيع البحث)
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141
Prevalence and trend of TPM by women background characteristics according to the survey year.
منشور في 2025الموضوعات: -
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S1 File -
منشور في 2025"…The study emphasizes the possibilities of knowledge distillation to produce effective models fit for use in resource-limited conditions, hence advancing NLP and mental health diagnosis. Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …"
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153
Confusion matrix for ClinicalBERT model.
منشور في 2025"…The study emphasizes the possibilities of knowledge distillation to produce effective models fit for use in resource-limited conditions, hence advancing NLP and mental health diagnosis. Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …"
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154
Confusion matrix for LastBERT model.
منشور في 2025"…The study emphasizes the possibilities of knowledge distillation to produce effective models fit for use in resource-limited conditions, hence advancing NLP and mental health diagnosis. Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …"
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155
Student model architecture.
منشور في 2025"…The study emphasizes the possibilities of knowledge distillation to produce effective models fit for use in resource-limited conditions, hence advancing NLP and mental health diagnosis. Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …"
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156
Configuration of the LastBERT model.
منشور في 2025"…The study emphasizes the possibilities of knowledge distillation to produce effective models fit for use in resource-limited conditions, hence advancing NLP and mental health diagnosis. Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …"
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157
Confusion matrix for DistilBERT model.
منشور في 2025"…The study emphasizes the possibilities of knowledge distillation to produce effective models fit for use in resource-limited conditions, hence advancing NLP and mental health diagnosis. Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …"
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158
ROC curve for LastBERT model.
منشور في 2025"…The study emphasizes the possibilities of knowledge distillation to produce effective models fit for use in resource-limited conditions, hence advancing NLP and mental health diagnosis. Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …"
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159
Sample Posts from the ADHD dataset.
منشور في 2025"…The study emphasizes the possibilities of knowledge distillation to produce effective models fit for use in resource-limited conditions, hence advancing NLP and mental health diagnosis. Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …"
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160
Top-level overview for ADHD classification study.
منشور في 2025"…The study emphasizes the possibilities of knowledge distillation to produce effective models fit for use in resource-limited conditions, hence advancing NLP and mental health diagnosis. Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …"