The major release of Spark NLP for Healthcare introduces a relation extraction annotator, based on a new deep learning model & utilizing BioBERT embeddings.
Medical imaging challenges were discussed in 2 previous blogs. The first blog gave an introductory brief about medical imaging, its different modalities, standards used (DICOM), efficiency measures, and what is...
One kind of noisy data that healthcare data scientists deal with is scanned documents and images: from PDF attachments of lab results, referrals, or genetic testing to DICOM files with...
Recent advances in deep learning enable automated de-identification of medical data to approach the accuracy achievable via manual effort. This includes accurate detection & obfuscation of patient names, doctor names,...
Demos
