activity
20142023
most citedMedCAT -- Medical Concept Annotation Tool

18 citations · 24 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2023★ 6 cited

Challenges and Opportunities of Using Transformer-Based Multi-Task Learning in NLP Through ML Lifecycle: A Survey

Lovre Torbarina, Tin Ferkovic, Lukasz Roguski +3

The increasing adoption of natural language processing (NLP) models across industries has led to practitioners' need for machine learning systems to handle these models efficiently…

cs.IR2021

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

Kawsar Noor, Lukasz Roguski, Alex Handy +9

As more healthcare organisations transition to using electronic health record (EHR) systems it is important for these organisations to maximise the secondary use of their data to s…

cs.CL2020

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

Zeljko Kraljevic, Thomas Searle, Anthony Shek +15

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

cs.CL2019★ 18 cited

MedCAT -- Medical Concept Annotation Tool

Zeljko Kraljevic, Daniel Bean, Aurelie Mascio +5

Biomedical documents such as Electronic Health Records (EHRs) contain a large amount of information in an unstructured format. The data in EHRs is a hugely valuable resource docume…

cs.DS2014

Disk-based genome sequencing data compression

Szymon Grabowski, Sebastian Deorowicz, Łukasz Roguski

Motivation: High-coverage sequencing data have significant, yet hard to exploit, redundancy. Most FASTQ compressors cannot efficiently compress the DNA stream of large datasets, si…