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22 results on '"Romao, Luis"'

3. Distinct virologic trajectories in chronic hepatitis B identify heterogeneity in response to nucleos(t)ide analogue therapy

Author

Barnes, Eleanor, Matthews, Philippa C., Gelson, William, Cooke, Graham S., Khakoo, Salim I., Nastouli, Eleni, Davies, Jim, Woods, Kerrie, Stockdale, Alexander J., Ryder, Stephen, Elsharkawy, Ahmed, Easom, Nicholas, Bernal, William, Ahmad, Shazaad, Macdonald, Douglas, Wang, Tingyan, Campbell, Cori, Stanworth, Simon, Maynard, Suzanne, Roadknight, Gail, Little, Stephanie, Várnai, Kinga A., Glampson, Ben, Papadimitriou, Dimitri, Mercuri, Luca, Jones, Christopher R., Jaworski, Jakub, Davis, Cai, Borca, Florina, Heinson, Ashley, George, Michael, MacNaughton, Heidi, Kim, Yun, Meneses, Josune Olza, English, Louise, Roberts, Timothy, Romão, Luis, Ramlakhan, David, Todd, Stacy, Rogers, Heather, McIntyre, Karl, Frankland, Andrew, Salih, Hizni, Noble, Theresa, Roberts, Lara, Higgins, Finola, Vilar, Javier, Norris, Ruth, Tilston, George, Serafimova, Ilina, Montague, Sarah, Verheyden, Juliette, Juurlink, Irene, Jack, Kathryn, Waldren-Glenn, Alex, Poole, Lizzie, Day, Victoria, Reglar, Berit, Mayer, Erik, and Heinson, Ashley I.

Published
2025
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4. Predicting Clinical Intent from Free Text Electronic Health Records

Author

Noor, Kawsar, Smith, Katherine, Bennett, Julia, OConnell, Jade, Fisk, Jessica, Hunt, Monika, Philippo, Gary, Xu, Teresa, Knight, Simon, Romao, Luis, Dobson, Richard JB, and Wong, Wai Keong

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

After a patient consultation, a clinician determines the steps in the management of the patient. A clinician may for example request to see the patient again or refer them to a specialist. Whilst most clinicians will record their intent as "next steps" in the patient's clinical notes, in some cases the clinician may forget to indicate their intent as an order or request, e.g. failure to place the follow-up order. This consequently results in patients becoming lost-to-follow up and may in some cases lead to adverse consequences. 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. Annotators systematically identified 22 possible types of clinical intent and annotated 3000 Bariatric clinical notes. The annotation process revealed a class imbalance in the labeled data and we found that there was only sufficient labeled data to train 11 out of the 22 intents. We used the data to train a BERT based multilabel classification model and reported the following average accuracy metrics for all intents: macro-precision: 0.91, macro-recall: 0.90, macro-f1: 0.90.

Published
2022

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

Author

Noor, Kawsar, Roguski, Lukasz, Handy, Alex, Klapaukh, Roman, Folarin, Amos, Romao, Luis, Matteson, Joshua, Lea, Nathan, Zhu, Leilei, Wong, Wai Keong, Shah, Anoop, and Dobson, Richard J

Subjects
Computer Science - Information Retrieval
Abstract

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 support service improvement and clinical research. These organisations will find it challenging to have systems which can mine information from the unstructured data fields in the record (clinical notes, letters etc) and more practically have such systems interact with all of the hospitals data systems (legacy and current). 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. The platform has improved data ingestion capabilities as well as better tools for natural language processing. To date we have processed over 18 million records and the insights produced from CogStack have informed a number of clinical research use cases at the hospitals.

Published
2021

8. A New Extended Perspective System for Architectural Drawings

Author

Correia, José Vitor, Romão, Luís, Ganhão, Susana Rosado, da Costa, Manuel Couceiro, Guerreiro, Ana Santos, Henriques, Diogo Pereira, Garcia, Sara, Albuquerque, Carlos, Carmo, Maria Beatriz, Cláudio, Ana Paula, Chambel, Teresa, Burgess, Robin, Marques, Christian, Zhang, Jianlong, editor, and Sun, Chengyu, editor

Published
2013
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9. Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital:CogStack at University College London Hospitals

Author

Noor, Kawsar, Roguski, Lukasz, Bai, Xi, Handy, Alex, Klapaukh, Roman, Folarin, Amos, Romao, Luis, Matteson, Joshua, Lea, Nathan, Zhu, Leilei, Asselbergs, Folkert W, Wong, Wai Keong, Shah, Anoop, and Dobson, Richard JB

Abstract

BACKGROUND: As more health care organizations transition to using electronic health record (EHR) systems, it is important for these organizations to maximize the secondary use of their data to support service improvement and clinical research. These organizations will find it challenging to have systems capable of harnessing the unstructured data fields in the record (clinical notes, letters, etc) and more practically have such systems interact with all of the hospital data systems (legacy and current).OBJECTIVE: We describe the deployment of the EHR interfacing information extraction and retrieval platform CogStack at University College London Hospitals (UCLH).METHODS: At UCLH, we have deployed the CogStack platform, an information retrieval platform with natural language processing capabilities. The platform addresses the problem of data ingestion and harmonization from multiple data sources using the Apache NiFi module for managing complex data flows. The platform also facilitates the extraction of structured data from free-text records through use of the MedCAT natural language processing library. Finally, data science tools are made available to support data scientists and the development of downstream applications dependent upon data ingested and analyzed by CogStack.RESULTS: The platform has been deployed at the hospital, and in particular, it has facilitated a number of research and service evaluation projects. To date, we have processed over 30 million records, and the insights produced from CogStack have informed a number of clinical research use cases at the hospital.CONCLUSIONS: The CogStack platform can be configured to handle the data ingestion and harmonization challenges faced by a hospital. More importantly, the platform enables the hospital to unlock important clinical information from the unstructured portion of the record using natural language processing technology.

Published
2022
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10. Portugal

Author

Romão, Luis

Published
2012

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

Author

Noor, Kawsar, primary, Roguski, Lukasz, additional, Bai, Xi, additional, Handy, Alex, additional, Klapaukh, Roman, additional, Folarin, Amos, additional, Romao, Luis, additional, Matteson, Joshua, additional, Lea, Nathan, additional, Zhu, Leilei, additional, Asselbergs, Folkert W, additional, Wong, Wai Keong, additional, Shah, Anoop, additional, and Dobson, Richard JB, additional

Published
2022
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12. Portugal

Author

Romão, Luís Miguel

Published
2011

14. TOP-417 Machine learning can improve prediction of hepatitis B surface antigen seroclearance: A large multicentre cohort study in the United Kingdom

Author

Wang, Tingyan, Jaworski, Jakub, Glampson, Ben, Papadimitriou, Dimitri, Mercuri, Luca, Jones, Christopher R., Todd, Stacy, McIntyre, Karl, Frankland, Andrew, Salih, Hizni, Roadknight, Gail, Little, Stephanie, Noble, Theresa, Várnai, Kinga A., Campbell, Cori, Davis, Cai, Heinson, Ashley I., George, Michael, Borca, Florina, English, Louise, Romão, Luis, Ramlakhan, David, Frisby, William, Taylor, John, Woods, Kerrie, Davies, Jim, Nastouli, Eleni, Khakoo, Salim I., Stockdale, Alexander J., Easom, Nicholas, Cooke, Graham S., Gelson, William, Matthews, Philippa C., and Barnes, Eleanor

Published
2024
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15. WED-471 Retrospective analysis of longitudinal data for UK adults living with chronic HBV: characteristics of the population on dual therapy

Author

Tan, Cedric, Wang, Tingyan, Jaworski, Jakub, Glampson, Ben, Papadimitriou, Dimitri, Mercuri, Luca, Jones, Christopher R, Todd, Stacy, McIntyre, Karl, Frankland, Andrew, Salih, Hizni, Roadknight, Gail, Little, Stephanie, Noble, Theresa, AVárnai, Kinga, Campbell, Cori, Davis, Cai, Heinson, Ashley I, George, Michael, Borca, Florina, English, Louise, Romão, Luis, Ramlakhan, David, Frisby, William, Taylor, John, Woods, Kerrie, Davies, Jim, Nastouli, Eleni, Khakoo, Salim I, Stockdale, Alexander J, Easom, Nicholas, Cooke, Graham S, Gelson, William, Barnes, Eleanor, and CMatthews, Philippa

Published
2024
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17. WED-137 - Distinct virologic trajectories in chronic hepatitis B patients identify heterogeneity in response to nucleotide analogue therapy

Author

Wang, Tingyan, Campbell, Cori, Roadknight, Gail, Little, Stephanie, Stockdale, Alexander, Todd, Stacy, McIntyre, Karl, Frankland, Andrew, Jaworski, Jakub, Chaudhry, Afzal, Glampson, Ben, Mercuri, Luca, Papadimitriou, Dimitri, Jones, Christopher R., Varnai, Kinga, Noble, Theresa, Salih, Hizni, Davis, Cai, Heinson, Ashley, George, Michael, Borca, Florina, Olza, Josune, English, Louise, Romão, Luis, Ramlakhan, David, Nastouli, Eleni, Khakoo, Salim, Gelson, Will, Cooke, Graham, Woods, Kerrie, Davies, Jim, Matthews, Philippa, and Barnes, Eleanor

Published
2023
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19. Natural Language Processing for Mimicking Clinical Trial Recruitment in Critical Care: A Semi-Automated Simulation Based on the LeoPARDS Trial

Author

Team Medisch, Circulatory Health, Tissot, Hegler C, Shah, Anoop D, Brealey, David, Harris, Steve, Agbakoba, Ruth, Folarin, Amos, Romao, Luis, Roguski, Lukasz, Dobson, Richard, Asselbergs, Folkert W, Team Medisch, Circulatory Health, Tissot, Hegler C, Shah, Anoop D, Brealey, David, Harris, Steve, Agbakoba, Ruth, Folarin, Amos, Romao, Luis, Roguski, Lukasz, Dobson, Richard, and Asselbergs, Folkert W

Published
2020

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