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LO-1
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Explain the basic concepts and application areas of natural language processing. |
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LO-2
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Apply text preprocessing techniques (tokenization, stemming, stop-word removal). |
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LO-3
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Describe the structure of clinical text and the characteristics of free-text data. |
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LO-4
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Extract clinical concepts using named entity recognition (NER). |
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LO-5
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Extract diagnosis, medication, and symptom information from clinical text. |
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LO-6
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Explain text classification and sentiment analysis methods. |
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LO-7
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Compare rule-based and statistical approaches in clinical text mining. |
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LO-8
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Explain the application of deep learning-based language models to clinical text. |
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LO-9
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Interpret the process of converting free text into structured data. |
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LO-10
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Evaluate data privacy and ethical issues in NLP applications. |