Validating transformers for redaction of text from electronic health records in real-world healthcare

1 code implementation • 5 Oct 2023 • Zeljko Kraljevic, Anthony Shek, Joshua Au Yeung, Ewart Jonathan Sheldon, Mohammad Al-Agil, Haris Shuaib, Xi Bai, Kawsar Noor, Anoop D. Shah, Richard Dobson, James Teo

Protecting patient privacy in healthcare records is a top priority, and redaction is a commonly used method for obscuring directly identifiable information in text.

Predicting Clinical Intent from Free Text Electronic Health Records

no code implementations • 25 Mar 2022 • Kawsar Noor, Katherine Smith, Julia Bennett, Jade OConnell, Jessica Fisk, Monika Hunt, Gary Philippo, Teresa Xu, Simon Knight, Luis Romao, Richard JB Dobson, Wai Keong Wong

In this paper we train a machine learning model to detect a clinician's intent to follow up with a patient from the patient's clinical notes.

Management

Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals

no code implementations • 15 Aug 2021 • Kawsar Noor, Lukasz Roguski, Alex Handy, Roman Klapaukh, Amos Folarin, Luis Romao, Joshua Matteson, Nathan Lea, Leilei Zhu, Wai Keong Wong, Anoop Shah, Richard J Dobson

To tackle this problem at University College London Hospitals, we have deployed an enhanced version of the CogStack platform; an information retrieval platform with natural language processing capabilities which we have configured to process the hospital's existing and legacy records.

Information Retrieval Retrieval

Multi-domain Clinical Natural Language Processing with MedCAT: the Medical Concept Annotation Toolkit

1 code implementation • 2 Oct 2020 • Zeljko Kraljevic, Thomas Searle, Anthony Shek, Lukasz Roguski, Kawsar Noor, Daniel Bean, Aurelie Mascio, Leilei Zhu, Amos A Folarin, Angus Roberts, Rebecca Bendayan, Mark P Richardson, Robert Stewart, Anoop D Shah, Wai Keong Wong, Zina Ibrahim, James T Teo, Richard JB Dobson

Electronic health records (EHR) contain large volumes of unstructured text, requiring the application of Information Extraction (IE) technologies to enable clinical analysis.