@inproceedings{df4ae94ad99548c690749b1e75262494,
title = "Synthetic Patient Perspective Data for the Curation and Evaluation of Rare Disease Patient-Facing Technology",
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 patient-facing technology within this area. A significant obstacle for research in this area is the lack of data which represents the patient{\textquoteright}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.",
keywords = "Data generation, Diagnosis, Health, Patient-facing technology, Rare disease, Synthetic data",
author = "Emily Nielsen and Tom Owen and Matthew Roach and Alan Dix",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 1st International Conference on Artificial Intelligence in Healthcare, AIiH 2024 ; Conference date: 04-09-2024 Through 06-09-2024",
year = "2024",
month = aug,
day = "15",
doi = "10.1007/978-3-031-67285-9_24",
language = "English",
isbn = "9783031672842",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "330--343",
editor = "Xianghua Xie and Gibin Powathil and Iain Styles and Marco Ceccarelli",
booktitle = "Artificial Intelligence in Healthcare - 1st International Conference, AIiH 2024, Proceedings",
}