In medicine, NLP (Natural Language Processing) is revolutionizing the way healthcare providers manage vast amounts of unstructured data, such as clinical notes, radiology reports, and patient histories. Unlike consumer applications...
Using machine learning and regex patterns to identify and extract date information in Spark NLP TL; DR: Dates extraction from a text is a common Natural Language Processing (NLP) task...
The social determinants of health (SDoH) are the non-medical factors that influence health outcomes and usually one of the hardest type of entities to extract with pre-trained clinical NLP models....
Creating visualizations for analysis and reporting using Spark NLP and Spark NLP display. TL;DR: Visualizing Named Entities is a technique for representing the results of named entity recognition (NER) in...
Use pretrained models, segment texts into words, and train custom word segmenter models with Python. TL; DR: Some Asian languages don’t separate words by white space like English, and NLP...
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