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Design, development and validation of a system for automatic help to medical text understanding

Alfano, Marco orcid logoORCID: 0000-0001-7200-9547, Lenzitti, Biagio orcid logoORCID: 0000-0003-2664-7788, Lo Bosco, Giosuè orcid logoORCID: 0000-0002-1602-0693, Muriana, Cinzia orcid logoORCID: 0000-0002-9951-1761, Piazza, Tommaso orcid logoORCID: 0000-0001-5881-1410 and Vizzini, Giovanni orcid logoORCID: 0000-0002-3273-1719 (2020) Design, development and validation of a system for automatic help to medical text understanding. International Journal of Medical Informatics, 138 . ISSN 1386-5056

Abstract
Objective: The paper presents a web-based application, SIMPLE, that facilitates medical text comprehension by identifying the health-related terms of a medical text and providing the corresponding consumer terms and explanations. Background: The comprehension of a medical text is often a difficult task for laypeople because it requires semantic abilities that can differ from a person to another, depending on his/her health-literacy level. Some systems have been developed for facilitating the comprehension of medical texts through text simplification, either syntactical or lexical. The ones dealing with lexical simplification usually replace the original text and do not provide additional information. We have developed a system that provides the consumer terms alongside the original medical terms and also adds consumer explanations. Moreover, differently from other solutions, our system works with multiple languages. Methods: We have developed the SIMPLE application that is able to automatically: 1) identify medical terms in a medical text by using medical vocabularies; 2) translate the medical terms into consumer terms through medicalconsumer thesauri; 3) provide term explanations by using health-consumer dictionaries. SIMPLE can be used as a standalone web application or can it be embedded into common health platforms for real time identification and explanation of medical terms. At present, it works with English and Italian texts but it can be easily extended to other languages. We have run subjective tests with both medical experts and non-experts as well as objective tests to verify the effectiveness of SIMPLE and its simplicity of use. Results: Non-experts found SIMPLE easy to use and responsive. The big majority of respondents confirmed they were helped by SIMPLE in understanding medical texts and declared their willingness to continue using SIMPLE and to recommend it to other people. The subjective tests, conducted with medical experts on a set of Italian radiology reports, showed an agreement between SIMPLE and the experts, on the highlighted medical terms, that ranges between 74.05 % and 81.16 % as well as an agreement of around 60 % on the consumer term translation. The objective tests showed that the consumer terms, provided by SIMPLE, are, on average, eighteen times more familiar than the relative medical terms so proving, once more, the effectiveness of SIMPLE in simplifying the medical terms. Conclusions: The performed tests demonstrate the effectiveness of SIMPLE, its simplicity of use and the willingness of people in continuing with its use. SIMPLE provides, with a good agreement level, the same information that medical experts would provide. Finally, the consumer terms are ‘objectively’ more familiar than the related technical terms and as a consequence, much easier to understand.
Metadata
Item Type:Article (Published)
Refereed:Yes
Additional Information:Article number 104109
Uncontrolled Keywords:e-health; Patient empowerment; Lexical simplification; Consumer health vocabulary; Term familiarity; Infobutton
Subjects:Computer Science > Information retrieval
Computer Science > World Wide Web
Medical Sciences > Health
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > Lero: The Irish Software Engineering Research Centre
Publisher:Elsevier
Official URL:https://doi.org/10.1016/j.ijmedinf.2020.104109
Copyright Information:© 2020 Elsevier
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 754489, Science Foundation Ireland grant 13/RC/2094, European Regional Development Fund through the Southern & Eastern Regional Operational Programme to Lero, the Science Foundation Ireland Research Centre for Software
ID Code:24682
Deposited On:25 Jun 2020 11:37 by Marco Alfano . Last Modified 03 Mar 2021 04:30
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