Lano, Kevin;
Tehrani, Sobhan Y.;
Umar, Mohammad;
Alwakeel, Lyan;
(2022)
Using Artificial Intelligence for the Specification of m-Health and e-Health Systems.
In: Ehsani, Sepehr and Glauner, Patrick and Plugmann, Philipp and Thieringer, Florian M., (eds.)
The Future Circle of Healthcare: AI, 3D Printing, Longevity, Ethics, and Uncertainty Mitigation.
(pp. 273-299).
Springer Nature: Cham, Switzerland.
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Abstract
Artificial intelligence (AI) techniques such as machine learning (ML) have wide application in medical informatics systems. In this chapter, we employ AI techniques to assist in deriving software specifications of e-Health and m-Health systems from informal requirements statements. We use natural language processing (NLP), optical character recognition (OCR), and machine learning to identify required data and behaviour elements of systems from textual and graphical requirements documents. Heuristic rules are used to extract formal specification models of the systems from these documents. The extracted specifications can then be used as the starting point for automated software production using model-driven engineering (MDE). We illustrate the process using an example of a stroke recovery assistant app and evaluate the techniques on several representative systems.
Type: | Book chapter |
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Title: | Using Artificial Intelligence for the Specification of m-Health and e-Health Systems |
ISBN-13: | 978-3-030-99837-0 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1007/978-3-030-99838-7_15 |
Publisher version: | https://doi.org/10.1007/978-3-030-99838-7_15 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
URI: | https://discovery.ucl.ac.uk/id/eprint/10157185 |
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