Exploring Named Entity Recognition Potential and the Value of Tailored Natural Language Processing Pipelines for Radiology, Pathology, and Progress Notes in Clinical Decision Support: Quantitative Study.

Veysel Kocaman¹, Fu-Yuan Cheng², Julio Bonis¹, Ganesh Raut², Prem Timsina², David Talby¹, Arash Kia³

¹John Snow Labs Inc, Lewes, DE, United States.

²Institute for Healthcare Delivery Science, Mount Sinai, New York, NY, United States.

³Department of Anesteshiology, Perioperative and Pain Medicine, Mount Sinai, New York, NY, United States.

PubMed PMC DOI PDF

Abstract

BACKGROUND: Clinical notes house rich, yet unstructured, patient data, making analysis challenging due to medical jargon, abbreviations, and synonyms causing ambiguity. This complicates real-time extraction for decision support tools. OBJECTIVE: This study aimed to examine the data curation, technology, and workflow of the named entity recognition (NER) pipeline, a component of a broader clinical…

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