Publications

Detailed Information

Mixed-Initiative Approach to Extract Data from Pictures of Medical Invoice

Cited 0 time in Web of Science Cited 2 time in Scopus
Authors

Jung, Seokweon; Choe, Kiroong; Park, Seokhyeon; Ko, Hyung-Kwon; Kim, Youngtaek; Seo, Jin Wook

Issue Date
2021-04
Publisher
IEEE
Citation
IEEE Pacific Visualization Symposium, Vol.2021-April, pp.111-115
Abstract
© 2021 IEEE.Extracting data from pictures of medical records is a common task in the insurance industry as the patients often send their medical invoices taken by smartphone cameras. However, the overall process is still challenging to be fully automated because of low image quality and variation of templates that exist in the status quo. In this paper, we propose a mixed-initiative pipeline for extracting data from pictures of medical invoices, where deep-learning-based automatic prediction models and task-specific heuristics work together under the mediation of a user. In the user study with 12 participants, we confirmed our mixed-initiative approach can supplement the drawbacks of a fully automated approach within an acceptable completion time. We further discuss the findings, limitations, and future works for designing a mixed-initiative system to extract data from pictures of a complicated table.
ISSN
2165-8765
URI
https://hdl.handle.net/10371/183749
DOI
https://doi.org/10.1109/PacificVis52677.2021.00022
Files in This Item:
There are no files associated with this item.
Appears in Collections:

Altmetrics

Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Share