What are Some Common NLP Techniques Used in Cancer Research?
Several NLP techniques are commonly used in cancer research:
Named Entity Recognition (NER): Identifies and classifies key entities such as drugs, symptoms, and diagnoses within the text. Sentiment Analysis: Analyzes text to determine the sentiment or emotional tone, which can be useful in understanding patient experiences and reviews of treatments. Text Classification: Categorizes text into predefined classes, such as identifying whether a clinical note relates to a specific type of cancer. Topic Modeling: Discovers the underlying themes or topics present in a corpus of documents, aiding in literature review and trend analysis. Machine Translation: Converts medical text from one language to another, facilitating international research collaborations.
