Many critical facts required by healthcare AI applications like patient risk prediction, cohort selection, and clinical decision support are locked in unstructured free-text data. Recent advances in deep learning have raised...
An AI-based solution that delivers a future-proof model using transfer learning which can be used to convert source-agnostic unstructured data into structured data. It supports the classification of artifacts and...
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...
A modern health care system generates a wide range of clinical data formats including structured, unstructured, image, and high-frequency waveform data. The volume of data is also growing quickly, enabling...
Medicare risk adjustment is a rule-based calculation, based on seven variables: ICD Codes of the patient’s diagnoses, age, gender, eligibility segment, entitlement reason, Medicaid status, and if the patient is...
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