llnl/al_nlp
Active Learning framework for Natural Language Processing of pathology reports.
This project helps medical researchers and data scientists efficiently categorize large volumes of unstructured pathology reports. It takes raw text from these reports and uses natural language processing to extract relevant attributes, even with limited labeled data. The output is categorized data, allowing researchers to quickly analyze specific medical conditions or characteristics.
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Use this if you need to classify medical text data, especially pathology reports, but have limited resources for manual data labeling.
Not ideal if your data is not text-based or if you require real-time classification with extremely high throughput.
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Dec 08, 2021
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