Kulev, Igor

Preferred name

Kulev, Igor

Official Name

Kulev, Igor

Main Affiliation

igor.kulev@finki.ukim.mk

Now showing 1 - 9 of 9

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Recommendation algorithm based on collaborative filtering and his application in health care
(2013)
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Vlahu-Gjorgievska, Elena
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Trajkovik, Vladimir
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Koceski, Saso
This paper presents a novel recommendation algorithm that generates recommendations and suggestions for preventive intervention. Presented algorithm is part of the Collaborative health care system model called COHESY. The purpose of recommendation algorithm is to give a recommendation for performing a specific activity that will improve user’s health, based on his given health condition and set of knowledge derived from the history of the user and users like him. The aim of the recommendation algorithm is to discover which activities affect change in the value of each health parameter individually. Once revealed, algorithm can use that information in situations it recognizes as same or similar to previous health conditions of a same or another user with similar medical condition. If there is evidence in users’ history, that the execution of a certain physical activity has improved user health parameters and condition, it can be concluded that the activity can help him or other users with similar health issues and improve their health condition. In this paper we also evaluate the proposed algorithm by using generic data.
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Connected-health algorithm: Development and evaluation
(Springer US, 2016-04)
Vlahu-Gjorgievska, Elena
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Koceski, Sasho
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Trajkovik, Vladimir
Nowadays, there is a growing interest towards the adoption of novel ICT technologies in the field of medical monitoring and personal health care systems. This paper proposes design of a connected health algorithm inspired from social computing paradigm. The purpose of the algorithm is to give a recommendation for performing a specific activity that will improve user’s health, based on his health condition and set of knowledge derived from the history of the user and users with similar attitudes to him. The algorithm could help users to have bigger confidence in choosing their physical activities that will improve their health. The proposed algorithm has been experimentally validated using real data collected from a community of 1000 active users. The results showed that the recommended physical activity, contributed towards weight loss of at least 0.5 kg, is found in the first half of the ordered list of recommendations, generated by the algorithm, with the probability > 0.6 with 1% level of significance.
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Evaluation of physical activities recommendation methodology for blood glucose level regulation
(Institute of Advanced Engineering and Science (IAES), 2014-12)
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Koceski, Sasho
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Vlahu-Gjorgievska, Elena
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Trajkovik, Vladimir
Providing patients with convenient health facilities at a low cost has always been a great challenge for health service providers. Moreover, the fast changing life style of the modern world and the problem of aging society pose an urgent need to modernize such facilities. The emphasis has to be paid on providing health monitoring in out-of-hospital conditions for elderly people and patients who require regular supervision, particularly in remote areas. This paper presents a recommendation algorithm, which incorporates collaboration and classification techniques in order to generate recommendations and suggestions for the physical activities that the users should carry out in order to improve their health. The algorithm has been evaluated using generic data and considering the daily food intake. The results of the experimental evaluation show that the algorithm is robust and could suggest the physical activities that might compensate the influence of the food intake over the blood glucose level.
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General assisted living system architecture model
(Springer International Publishing, 2015)
Trajkovik, Vladimir
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Vlahu-Gjorgievska, Elena
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Koceski, Sasho
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Novel information and communication technologies create possibilities to change the future of health care and support. Ambient Assisted Living (AAL) is seen as a promising alternative to the current care models so a number of researchers have developed AAL systems with promising results. The main goal of AAL solutions is to apply ambient intelligence technologies to enable people with specific needs to continue to live in their preferred environments. In this paper we are presenting a general architecture of system for assisted living that supports most of the use cases for such system.
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Use of collaboration techniques and classification algorithms in personal healthcare
(Springer-Verlag, 2012-04)
Trajkovik, Vladimir
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Vlahu-Gjorgievska, Elena
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Adoption of mobile devices and technology in the field of medical monitoring and personal health care systems is very important nowadays, especially when it comes to certain categories of people with chronicle diseases who need 24 hour access to medical care. The collaborative Information system model we present in this paper, gives a new dimension in the usage of novel technologies in healthcare. Using mobile, web and broadband technologies enable the citizens to have ubiquity of support services where ever they may be. The model incorporates collaboration techniques and classification algorithms in order to generate recommendations and suggestions for preventive intervention. In addition, the system enables the patient (system user) to contact other people with similar condition and exchange their experience. This system improves the terms of home care treatment of the patient and allows the user to adapt his/ her physical activities to improve own health condition.
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Text Classification Using Semantic Networks
(Institute of Informatics, Skopje, Macedonia, 2011-03)
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Jovanovik, Milos
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In the age of information overflow, we face with the challenge of categorizing the digital information we come across on a daily basis, in order to apply different operations and priorities to different types of information and to manage to use it in a more efficient manner. This issue introduces the challenge of automatic text classification. The problem of text classification can be defined as assigning one or more categories to a certain text, based on its contents. There are many different approaches for solving this problem: one of the solutions is the use of latent semantic analysis (LSA), statistical text analysis, etc. This paper introduces an algorithm for text classification with the use of semantic networks. In this paper we present a method for knowledge representation needed for this type of text analysis. We also show how to create this knowledge representation and how to use it to assign one or more categories to a given text.
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Evaluating an ordered list of recommended physical activities within health care system
(Springer International Publishing, 2015)
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Vlahu-Gjorgievska, Elena
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Koceski, Saso
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Trajkovik, Vladimir
Information and communication technologies make it possible to bridge the gap and time barriers in the flow of health information and knowledge, allowing every involved part in the health process to have access to the information. This approach provides the knowledge of the individual to contribute effectively to the improvement in human health. But also, helps the collective knowledge effectively to solve health problems on individual level. In this paper we are evaluating the algorithm that generates recommendation for users. We are using simulations on generic data to see how different types of activities are affecting the accuracy of the algorithm. On the basis of the performed activities and blood glucose measurements, our recommendation algorithm should determine list of activities that have bigger influence on the change of the blood glucose levels. Generic data for our simulations are based on modeling of food intake and physical activity influence over the blood glucose level
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Evaluation of health care system model based on collaborative algorithms
(Springer International Publishing, 2015)
Trajkovik, Vladimir
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Koceski, Sasho
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Vlahu-Gjorgievska, Elena
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Analysis of the recommendation algorithm in COHESY
(2013)
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Vlahu-Gjorgievska, Elena
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Koceski, Sasho
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Pervasive health care takes steps to design, develop, and evaluate computer technologies that help citizens participate more closely in their own healthcare, on one hand, and on the other to provide flexibility in the life of patient who lead an active everyday life with work, family and friends. This paper presents a novel collaborative algorithm that generates recommendations and suggestions for preventive intervention. The main purpose of this algorithm is to find the dependency of the users’ health condition and physical activities he/she performs. The recommendation algorithm, presented in this paper, is part of the Collaborative health care system model called COHESY. COHESY improves quality of care and life to its users, by offering freedom to enjoy life with the confidence that a medical professional is monitoring theirs health condition.

Kulev, Igor

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