Recommending Relevant Services in Electronic and Mobile Health Platforms

Gjorgji Noveski, Jakob Valič


Electronic and mobile health (EMH) is becoming an integrated part of healthcare as we move in the future. The opportunity in bringing closer healthcare services with the advent of the internet is growing larger. This is why it is important to adequately provide those services to the people that need them and to also further improve them. Regarding electronic and mobile healthcare systems, it is fairly easy for users to get lost while searching for some information due to the vast amount of data that is present for different illnesses, healthcare institutions and healthcare services. In this paper we present a platform that provides various healthcare services to people, namely the Insieme platform (ISE-EMH). Knowing the difficulty of finding relevant information on platforms and that user preferences vary to a great extent, we additionally give an overview of an implementation of the recommendation system that is part of the Insieme platform which helps users pick services that might be relevant to them.

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A. M. Alharbi, N. T. Alharbi, H. M. Alharbi, and D. M. Ibrahim (2019). Patient Assistance System: A Proposed Structure. 10th International Conference on Information and Communication Systems (ICICS), pp. 230–233,

R. D. Croon, L. V. Houdt, N. N. Htun, G. Štiglic, V. V. Abeele, and K. Verbert (2021). Health recommender systems: systematic review. Journal of Medical Internet Research, vol. 23, no. 6, article no. 18035,

A. Hommersom, P. J.F. Lucas, M. Velikova, G. Dal, J. Bastos, J. Rodriguez, M. Germs, and H. Schwietert (2013). MoSHCA-my mobile and smart health care assistant. 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013), pp. 188–192,

ISE-EMH, Interreg Italia-Slovenia project, Accessed July 13, 2022.

M. Kula (2015). Metadata embeddings for user and item cold-start recommendations. Proceedings of the 2nd Workshop on New Trends on Content-Based Recommender Systems co-located with 9th ACM Conference on Recommender Systems (RecSys 2015), vol. 1448, pp. 14–21,

R. Manne and S. C Kantheti (2021). Application of artificial intelligence in healthcare: chances and challenges. Current Journal of Applied Science and Technology, vol. 40, no. 6, pp. 78–89,

J. G. D. Ochoa, O. Csiszar, and T. Schimper (2021). Medical recommender systems based on continuous-valued logic and multi-criteria decision operators, using interpretable neural networks. BMC medical informatics and decision making, vol. 21, no. 1, pp. 1–15,

Sudhanshu, N. S. Punn, S. K. Sonbhadra, and S. Agarwal (2021). Recommending best course of treatment based on similarities of prognostic markers. International Conference on Neural Information Processing, pp. 393–404,

T. N. T. Tran, A. Felfernig, C. Trattner, and A. Holzinger (2021). Recommender systems in the healthcare domain: state-of-the-art and research issues. Journal of Intelligent Information Systems, vol. 57, no. 1, pp. 171–201,


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