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Synthetic Patient Perspective Data for the Curation and Evaluation of Rare Disease Patient-Facing Technology

Emily Nielsen Orcid Logo, Tom Owen Orcid Logo, Matt Roach Orcid Logo, Alan Dix Orcid Logo

Lecture Notes in Computer Science, Volume: 14976, Pages: 330 - 343

Swansea University Authors: Tom Owen Orcid Logo, Matt Roach Orcid Logo

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DOI (Published version): 10.1007/978-3-031-67285-9_24

Abstract

Patient-facing technology to support rare disease patients seeking diagnosis has received comparatively little focus from the literature, despite the recognition of its importance. We hypothesise that this is due to the challenges presented when designing pre-diagnostic patientfacing technology with...

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Published in: Lecture Notes in Computer Science
ISBN: 9783031672842 9783031672859
ISSN: 0302-9743 1611-3349
Published: Cham Springer Nature Switzerland 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa67635
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last_indexed 2024-11-25T14:20:31Z
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spelling 2024-09-12T11:38:11.2803793 v2 67635 2024-09-10 Synthetic Patient Perspective Data for the Curation and Evaluation of Rare Disease Patient-Facing Technology 9c68c1446c7e729b181aa579b3661b55 0000-0002-5150-0246 Tom Owen Tom Owen true false 9722c301d5bbdc96e967cdc629290fec 0000-0002-1486-5537 Matt Roach Matt Roach true false 2024-09-10 MACS Patient-facing technology to support rare disease patients seeking diagnosis has received comparatively little focus from the literature, despite the recognition of its importance. We hypothesise that this is due to the challenges presented when designing pre-diagnostic patientfacing technology within this area. A significant obstacle for research in this area is the lack of data which represents the patient’s perspective.Existing data typically does not present the temporal aspects of diagnosis which are crucial to evaluate the diagnosis time of technology and consists of clinical terminology which is not representative of patients. This work aims to bridge this gap by creating open-source data which: (i) utilises patient-friendly terms and (ii) facilitates the sequencing of phenotypes to temporally recreate the informational journey of a rare disease patient. Therefore, this work facilitates evaluations on whether pre-diagnostic technology reduces the time to a rare disease diagnosis, thus providing more meaningful metrics for success Book chapter Lecture Notes in Computer Science 14976 330 343 Springer Nature Switzerland Cham 9783031672842 9783031672859 0302-9743 1611-3349 Rare disease · Patient-facing technology · Diagnosis · Health · Synthetic data · Data generation 15 8 2024 2024-08-15 10.1007/978-3-031-67285-9_24 http://dx.doi.org/10.1007/978-3-031-67285-9_24 Artificial Intelligence in Healthcare, First International Conference, AIiH 2024, Swansea, UK, September 4–6, 2024, Proceedings, Part II. COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University The authors would like to thank Amicus Therapeutics for their support during this project. The main author is funded by the EPSRC Centre for Doctoral Training in Enhancing Human Interactions and Collaborations with Data and Intelligence Driven Systems (EP/S021892/1) 2024-09-12T11:38:11.2803793 2024-09-10T15:15:15.3178013 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Emily Nielsen 0000-0003-2389-541x 1 Tom Owen 0000-0002-5150-0246 2 Matt Roach 0000-0002-1486-5537 3 Alan Dix 0000-0002-5242-7693 4 67635__31297__d75f8718a93e46af82f3e4843b545a3f.pdf AiiH_Paper.AAM.pdf 2024-09-12T11:12:56.5763341 Output 8448504 application/pdf Accepted Manuscript true Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy true eng https://creativecommons.org/licenses/by/4.0/
title Synthetic Patient Perspective Data for the Curation and Evaluation of Rare Disease Patient-Facing Technology
spellingShingle Synthetic Patient Perspective Data for the Curation and Evaluation of Rare Disease Patient-Facing Technology
Tom Owen
Matt Roach
title_short Synthetic Patient Perspective Data for the Curation and Evaluation of Rare Disease Patient-Facing Technology
title_full Synthetic Patient Perspective Data for the Curation and Evaluation of Rare Disease Patient-Facing Technology
title_fullStr Synthetic Patient Perspective Data for the Curation and Evaluation of Rare Disease Patient-Facing Technology
title_full_unstemmed Synthetic Patient Perspective Data for the Curation and Evaluation of Rare Disease Patient-Facing Technology
title_sort Synthetic Patient Perspective Data for the Curation and Evaluation of Rare Disease Patient-Facing Technology
author_id_str_mv 9c68c1446c7e729b181aa579b3661b55
9722c301d5bbdc96e967cdc629290fec
author_id_fullname_str_mv 9c68c1446c7e729b181aa579b3661b55_***_Tom Owen
9722c301d5bbdc96e967cdc629290fec_***_Matt Roach
author Tom Owen
Matt Roach
author2 Emily Nielsen
Tom Owen
Matt Roach
Alan Dix
format Book chapter
container_title Lecture Notes in Computer Science
container_volume 14976
container_start_page 330
publishDate 2024
institution Swansea University
isbn 9783031672842
9783031672859
issn 0302-9743
1611-3349
doi_str_mv 10.1007/978-3-031-67285-9_24
publisher Springer Nature Switzerland
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url http://dx.doi.org/10.1007/978-3-031-67285-9_24
document_store_str 1
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description Patient-facing technology to support rare disease patients seeking diagnosis has received comparatively little focus from the literature, despite the recognition of its importance. We hypothesise that this is due to the challenges presented when designing pre-diagnostic patientfacing technology within this area. A significant obstacle for research in this area is the lack of data which represents the patient’s perspective.Existing data typically does not present the temporal aspects of diagnosis which are crucial to evaluate the diagnosis time of technology and consists of clinical terminology which is not representative of patients. This work aims to bridge this gap by creating open-source data which: (i) utilises patient-friendly terms and (ii) facilitates the sequencing of phenotypes to temporally recreate the informational journey of a rare disease patient. Therefore, this work facilitates evaluations on whether pre-diagnostic technology reduces the time to a rare disease diagnosis, thus providing more meaningful metrics for success
published_date 2024-08-15T08:33:38Z
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