De-identified Health Information to Improve Patient Care Modern-day wise folks say that “data is the new oil”. Data supports cutting-edge research, drives innovation, and helps with the development of solutions...
Providence St. Joseph Health’s (PSJH) unstructured data de-identification methodology relies on pre-trained BiLSTM-CNN-Char NER models provided by John Snow Labs. The PSJH Data science department evaluated John Snow Labs models...
The ability to extract clinical information at large scale and in real time from unstructured clinical notes is becoming a mission critical capability for IQVIA. Key data elements like tumor...
Introduction With evermore personal data being produced and stored by organizations, data privacy is becoming an increasing priority. Businesses have access to a lot of sensitive information about their customers,...
Spark NLP for Healthcare 3.1 improves the accuracy, functionality, and ease of use of the library’s data de-identification capabilities, whose are crutial for natural language processing in healthcare. All improvements...
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