BERT finetuned on NER downstream tasks
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Updated
Jun 12, 2023 - Python
BERT finetuned on NER downstream tasks
Набор инструментов для обработки радиобиологических Excel‑данных: визуализация опухолевого роста и кожных реакций, статистика, интерактивный GUI (PyQt6). Поддерживается оценка параметров LQ‑модели (α/β) и сравнение экспериментов.
Three different basic data analysis processes of biomedical data for Python. Level: beginner (~200 lines of pure code).
Multiclass classification of breast cancer subtypes using synthetic gene expression data. Refactored code to use a single function for model evaluation across Logistic Regression, Random Forest, and HistGradientBoosting, including metrics and ROC-AUC with Youden’s J statistic.
Multiclass classification of breast cancer subtypes using gene expression profiles. Evaluated and compared multiple models (Logistic Regression, Random Forest, HistGradientBoosting) using classification metrics, confusion matrices, and ROC-AUC analysis with Youden’s J statistic on synthetically generated data
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