Abstract
The aim of this study is to investigate the similarities of drug shapes for preventing medical accidents due to similar appearances. According to the Medical Error Corrective Guidance published by the Korea Ministry of Health and Welfare’s policy team, a number of pairs of medicine that should be treated carefully in order to prevent confusion. However, systematic investigation on which morphological factors cause confusion is not enough yet. In this study, investigated human’s perception of similar drugs experimentally. As the first step, 15,000 tablet images were collected from the Korea Food & Drug Administration’s online medicine library. Among them, 100 randomly selected images were used for card sorting experiment to construct a similarity matrix. The tablets were classified into several groups based on the similarity score analyzed by multidimensional scaling (MDS). The result showed that people have a tendency to classify tablets by shape, color, size and material.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Kohn, L.T., Corrigan, J., Donaldson, M.S.: Institute of Medicine (US) Committee on Quality of Health Care in America. To Error is Human: Building a Safer Health System. National Academy Press, Washington, DC (1999)
Rich, D.S.: A process for interpreting data on adverse drug events: determining optimal target levels. Clin. Ther. 20(Suppl. C), C59–C71 (1998)
U.S. Pharmacopeia 8th Annual MEDMARX Report Indicates Look-Alike/Sound-Alike Drugs Lead to Thousands of Medication Errors Nationwide. http://www.usp.org/search/site/medication%20error%20reporting. Accessed 7 Apr 2012
Ministry of Health and Welfare: Guidelines for Preventing Medication Error. Ministry of Health and Welfare, Gwacheon, pp. 91–93 (2008)
Emmerton, L.M., Rizk, M.F.S.: Look-alike and soundalike medicines: risks and solutions. Int. J. Clin. Pharm. 34, 4–8 (2012)
Lee, Y.B., Park, U., Jain, A.K.: PILL-ID matching and retrieval of drug pill imprint images. In: 20th International Conference on Pattern Recognition (ICPR), pp. 2632–2635 (2010)
Yu, C.C., Wen, C.Y., Lu, C.P., Chen, Y.F.: The drug tablet image retrieval system based on content-based image retrieval. Int. J. Innov. Comput. Inf. Control 8(7(A)), 4497–4508 (2012)
Ministry of Food and Drug Safety Republic of Korea. http://drug.mfds.go.kr/html/index.j. Accessed 2018
Annasaro, E., Hema, A.: Color and shape feature extraction and matching in pill identification systems. Int. J. Comput. Sci. Inf. Technol. 5(2), 1011–1015 (2014)
Tversky, A.: Features of similarity. Psychol. Rev. 85, 327–352 (1977)
Gärdenfors, P.: How to make the semantic web more semantic. In: Varzi, A., Vieu, L. (eds.) Formal Ontology in Information Systems, Proceedings of the Third International Conference (FOIS 2004). Frontiers in Artificial Intelligence and Applications, vol. 114, pp. 153–164. IOS Press, Amsterdam (2004)
Johannesson, M.: Combining integral and separable subspaces. In: Moore, J.D., Stenning, K. (eds.) Proceedings of the Twenty-Third Annual Conference of the Cognitive Science Society, pp. 447–452. Lawrence Erlbaum (2001)
Steyvers, M., Busey, T.: Predicting similarity ratings to faces using physical descriptions. In: Wenger, M., Townsend, J. (eds.) Computational, Geometric, and Process Perspectives on Facial Cognition: Contexts and Challenges. Lawrence Erlbaum Associates, pp. 1–18 (2000)
Huang, J., Kahana, M.J., Sekuler, R.: Similarity effects in name-face recognition: a dual-process, summed-similarity account (2012). https://pdfs.semanticscholar.org/ee95/0c60f57f9d4290186c0c59b8d997ffb4260b.pdf/access. Accessed 30 July 2018
Schwering, A., Raubal, M.: Measuring semantic similarity between geospatial conceptual regions. In: Lecture Notes in Computer Science, vol. 3799, pp. 90–106 (2005)
Healey, C.G.: Choosing effective colours for data visualization. Proc. IEEE Vis. 493, 263–270 (1996)
Bonnel, A., Prinzmetal, W.: Dividing attention between the color and the shape of objects. Percept. Psychophys. 60, 113–124 (1998)
Rogowitz, B.E., Frese, T., Smith, J., Bouman, C.A., Kalin, E.: Perceptual image similarity experiments. In: Proceedings of IS&T/SPIE Conference on Human Vision Electronic Imaging III, San Jose, CA, pp. 576–590 (1998)
Viviani, P., Aymoz, C.: Colour, form, and movement are not perceived simultaneously. Vis. Res. 41, 2909–2918 (2001). https://doi.org/10.1016/S0042-6989(01)00160-2
Torres, G.J., Basnet, R.B., Sung, A.H., Mukkamala, S., Ribeiro, B.M.: A similarity measure for clustering and its applications. Int. J. Elect. Comput. Syst. Eng. 3, 164–170 (2009)
Bock, H.H.: Multidimensional scaling in the framework of cluster analysis. In: Hermes, H.J., Optiz, O., Degens, P.O. (eds.) Studien zur Klassifikation: [Classification and its Environment], vol. 17, pp. 247–258. INDEKS-Verlag, Frankfurt (1986)
Acknowledgement
This study is supported by National Research Foundation of Korea (No. 2017R1D1A1B03032632).
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Kim, J., Park, M., Kim, C., Choi, E., Kim, B., Park, T. (2020). Classification of Similarity-Looking Drugs by Human Perception. In: Ahram, T., Falcão, C. (eds) Advances in Usability and User Experience. AHFE 2019. Advances in Intelligent Systems and Computing, vol 972. Springer, Cham. https://doi.org/10.1007/978-3-030-19135-1_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-19135-1_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-19134-4
Online ISBN: 978-3-030-19135-1
eBook Packages: EngineeringEngineering (R0)