The field of natural language processing (NLP) is rapidly advancing, and accurate clinical and biomedical NLP models are becoming increasingly important. In this keynote speech, Veysel will present a detailed...
This talk examines the crucial need for de-identifying protected health information (PHI) in unstructured patient-level data to harness its potential while ensuring compliance with legal and privacy requirements. With an...
PHI De-Identification with State-of-the-Art NLP De-identification for natural language processing in healthcare is a critical procedure for safeguarding Protected Health Information (PHI) within clinical notes, wherein the data is anonymized...
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....
Voice of Patients (VoP) NER, a brand-new Named Entity Recognition (NER) model released by John Snow Labs, can extract clinical entities from patient forums much better than any other clinical...
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