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Web-Based Expert System Design and Implementation for Personal Nutrition Planning

Yıl 2022, Cilt: 6 Sayı: 1, 1 - 12, 30.06.2022
https://doi.org/10.33461/uybisbbd.1013012

Öz

Recently, expert systems have been used in different fields for different purposes in order to respond to the changing user needs with the rapid development of information and communication technologies. The most important of these can be listed as interpretation, prediction, diagnosis, design, planning, imaging, debugging, maintenance, education and control. With the increase in the use of expert systems in the field of healthcare, expert systems are not only used for diagnosis and treatment, but also act as a decision support system. Today, there are many software and approaches for nutrition program planning on the basis of nutrition-oriented practices. In particular, rule-based or case-based expert systems are frequently used in the field of nutrition. The aim of the research is to develop a web-based expert system prototype in the field of nutrition with a rule-based system approach using the Prolog development environment. For this purpose, because of clear and neat syntax, one of the expert system programming languages based on "first order predicate calculus" that is Prolog, PHP for web and in the design phase; Bootstrap framework were preferred. For data visualization, data is retrieved from MySQL database. The application developed within the scope of the research is expected to contribute to the efficient implementation of nutrition planning, especially for institutions with insufficient human experts. In this sense, a system that offers personalized nutrition program recommendations for people of different ages, genders, heights, weights and therefore different body mass indexes has been developed. Thus, considering the benefits of proper nutrition, it is expected that the developed system will help the dietitian in the process of determining the nutrition program/meal planning, and for the patients in the processes of maintaining and monitoring it.

Kaynakça

  • Al-Dhuhli, B. A., Al-Gadidi, B. S., Al-Alawi, H. H., Al-Busaidi, K. A. (2013, June). Developing a Nutrition and Diet Expert System Prototype. In 21st International Business Information Management Association Conference.
  • Allahverdi, N. (2002). Uzman Sistemler: Bir Yapay Zeka Uygulaması. Atlas Yayın Dağıtım. İstanbul.
  • Behrman, J. R., Deolalikar, A. B. (1988). “Health and Nutrition”. Handbook of Development Economics, 1, 631-711.
  • Chen, Y., Hsu, C. Y., Liu, L., Yang, S. (2012). “Constructing a Nutrition Diagnosis Expert System”. Expert Systems with Applications, 39(2), 2132-2156.
  • Cioara, T., Anghel, I., Salomie, I., Barakat, L., Miles, S., Reidlinger, D., Taweel, A., Dobre, C., Pop, F. (2018). “Expert System for Nutrition Care Process of Older Adults”. Future Generation Computer Systems, 80, 368-383.
  • Gupta, M., Bhattacharjee, P. (2018). “DANES: Diet and Nutrition Expert System for Meal Management and Nutrition Counseling”. International Journal on Recent and Innovation Trends in Computing and Communication, 5(12), 204-208.
  • Hazman, M., & Idrees, A. M. (2015, November). A Healthy Nutrition Expert System for Children. In 2015 E-Health and Bioengineering Conference (EHB) (pp. 1-4). IEEE.
  • Heathfield, H. (1999). “The Rise And ‘Fall’ of Expert Systems in Medicine”. Expert Systems, 16(3), 183-188.
  • Hong, S. M., Kim, G. (2005). “Web Expert System for Nutrition Counseling and Menu Management”. Journal of Community Nutrition, 7(2), 107-113.
  • İçen, D., Günay, S. (2014). “Uzman Sistemler ve İstatistik”. İstatistikçiler Dergisi: İstatistik ve Aktüerya, 7(2), 37-45.
  • Kovasznai, G. (2011). Developing an Expert System for Diet Recommendation. 6th IEEE International Symposium on Applied Computational Intelligence and Informatics IEEE. 505-509.
  • Lu, M. T., Lu, D. H. (1992). “Neurocomputing Approach to Residential Property Valuation”. Journal of Organizational and End User Computing (JOEUC), 4(2), 21-30.
  • Lu, M., Mooney, S. P. (1989). “Assessing Expert SystemApplications: A Case Study”. International Journal of Information Management, 9, 267-273.
  • Ma’aruf, L. M., Garba, M. (2012). “Design and Implementation of an Expert Diet Prescription System”. International Journal of Artificial Intelligence and Expert Systems (IJAE), 3(4), 126-134.
  • Merrell, J., Philpin, S., Warring, J., Hobby, D., Gregory, V. (2012). “Addressing The Nutritional Needs of Older People in Residential Care Homes”. Health & Social Care in the Community, 20(2), 208-215.
  • Merritt, D. (2012). Building Expert Systems in Prolog. Springer Science & Business Media.
  • Metaxiotis, K. S., Samouilidis, J. E. (2000). “Expert Systems in Medicine: Academic Exercise or Practical Tool?”. Journal of Medical Engineering & Technology, 24(2), 68-72.
  • Mustafa, N., Hadi, A., Samsiah, N., Izham, M., Zawawi, A., Ahmad, A. (2020). iDietScore: Meal Recommender System for Athletes and Active Individuals. IJACSA, 11, 12.
  • Nowak, M., Szewczyk, J. (2021). Expert Systems in Medicine. The Book of Articles, 84.
  • Ojokoh, B., Babalola, A. (2016). “A Personalized Healthy Diet Recommender System”. Organization for Women in Science for the Developing World (OWSD), 388-393.
  • Pac, M., Mikutskaya, I., Mulawka, J. (2021). “Knowledge Discovery from Medical Data and Development of an Expert System in Immunology”. Entropy, 23(6), 695.
  • Rajeev, S., Krishnamoorthy, C. S. (1996). Artificial Intelligence and Expert Systems for Engineers. CRC Press.
  • Toledo, R. Y., Alzahrani, A. A., Martinez, L. (2019). “A Food Recommender System Considering Nutritional Information and User Preferences”. IEEE Access, 7, 96695-96711.
  • Turkish Ministry of Health, Directorate General of Public Health (2017). Yeterli ve Dengeli Beslenme Nedir?. https://hsgm.saglik.gov.tr/tr/beslenme/yeterli-ve-dengeli-beslenme-nedir.html. 16.10.2021.
  • van der Merwe A., Kruger H., Steyn T. (2015). “A Diet Expert System Utilizing Linear Programming Models in a Rule-based Inference Engine”. Journal of Applied Operational Research. 7(1):13–22. Whitney, E., Rolfes, S. R. (2018). Understanding Nutrition. Cengage Learning.

Kişisel Beslenme Planlamasina Yönelik Web Tabanli Uzman Sistem Tasarimi ve Uygulamasi

Yıl 2022, Cilt: 6 Sayı: 1, 1 - 12, 30.06.2022
https://doi.org/10.33461/uybisbbd.1013012

Öz

Son zamanlarda, bilgi ve iletişim teknolojilerinin hızlı gelişimi ile değişen kullanıcı gereksinimlerine cevap vermek için uzman sistemler farklı alanlarda, farklı amaçlarla kullanılmaktadır. Bunlardan en önemlileri, yorumlama, tahmin, teşhis, tasarım, planlama, görüntüleme, hata ayıklama, tamir, eğitim ve kontrol olarak listelenebilir. Sağlık alanında uzman sistemlerin kullanımının artışıyla birlikte, uzman sistemler sadece tanı ve tedavi amaçlı uygulanmayıp, aynı zamanda bir karar destek sistemi görevi yürütmektedirler. Günümüzde beslenme odaklı uygulamalar temelinde beslenme programı planlaması için çok sayıda yazılım ve yaklaşım bulunmaktadır. Özellikle kural tabanlı veya vaka tabanlı uzman sistemler, beslenme alanında sıklıkla kullanılmaktadır. Çalışmanın amacı, Prolog geliştirme ortamı kullanılarak kural tabanlı sistem yaklaşımı ile beslenme alanında web tabanlı bir uzman sistem prototipi geliştirmektir. Bu amaçla uzman sistem programlama dillerinden temeli “first order predicate calculus” a dayanan ve anlaşılır, düzgün bir söz dizimine sahip olduğundan Prolog programlama dili, web tarafında PHP ve tasarım aşamasında Bootstrap frameworkü tercih edilmiştir. Veri görselleştirme için veriler MySQL veritabanından çekilmektedir. Çalışma kapsamında geliştirilen uygulamanın özellikle yetersiz uzmana sahip olan kurumlar için beslenme planlamasının verimli bir şekilde gerçekleşmesine katkıda bulunması beklenmektedir. Bu anlamda, çalışmada farklı yaş, cinsiyet, boy, kilo ve dolayısıyla farklı vücut kitle endeksine sahip kişiler için kişiselleştirilmiş beslenme programı önerileri sunan bir sistem geliştirilmiştir. Böylelikle doğru beslenmenin yararları göz önünde bulundurulduğunda, geliştirilen sistemin diyetisyen için beslenme programı/öğün planlaması belirleme sürecinde, hastalar için ise bunu sürdürme ve izlenebilir kılma süreçlerinde yardımcı olması beklenmektedir

Kaynakça

  • Al-Dhuhli, B. A., Al-Gadidi, B. S., Al-Alawi, H. H., Al-Busaidi, K. A. (2013, June). Developing a Nutrition and Diet Expert System Prototype. In 21st International Business Information Management Association Conference.
  • Allahverdi, N. (2002). Uzman Sistemler: Bir Yapay Zeka Uygulaması. Atlas Yayın Dağıtım. İstanbul.
  • Behrman, J. R., Deolalikar, A. B. (1988). “Health and Nutrition”. Handbook of Development Economics, 1, 631-711.
  • Chen, Y., Hsu, C. Y., Liu, L., Yang, S. (2012). “Constructing a Nutrition Diagnosis Expert System”. Expert Systems with Applications, 39(2), 2132-2156.
  • Cioara, T., Anghel, I., Salomie, I., Barakat, L., Miles, S., Reidlinger, D., Taweel, A., Dobre, C., Pop, F. (2018). “Expert System for Nutrition Care Process of Older Adults”. Future Generation Computer Systems, 80, 368-383.
  • Gupta, M., Bhattacharjee, P. (2018). “DANES: Diet and Nutrition Expert System for Meal Management and Nutrition Counseling”. International Journal on Recent and Innovation Trends in Computing and Communication, 5(12), 204-208.
  • Hazman, M., & Idrees, A. M. (2015, November). A Healthy Nutrition Expert System for Children. In 2015 E-Health and Bioengineering Conference (EHB) (pp. 1-4). IEEE.
  • Heathfield, H. (1999). “The Rise And ‘Fall’ of Expert Systems in Medicine”. Expert Systems, 16(3), 183-188.
  • Hong, S. M., Kim, G. (2005). “Web Expert System for Nutrition Counseling and Menu Management”. Journal of Community Nutrition, 7(2), 107-113.
  • İçen, D., Günay, S. (2014). “Uzman Sistemler ve İstatistik”. İstatistikçiler Dergisi: İstatistik ve Aktüerya, 7(2), 37-45.
  • Kovasznai, G. (2011). Developing an Expert System for Diet Recommendation. 6th IEEE International Symposium on Applied Computational Intelligence and Informatics IEEE. 505-509.
  • Lu, M. T., Lu, D. H. (1992). “Neurocomputing Approach to Residential Property Valuation”. Journal of Organizational and End User Computing (JOEUC), 4(2), 21-30.
  • Lu, M., Mooney, S. P. (1989). “Assessing Expert SystemApplications: A Case Study”. International Journal of Information Management, 9, 267-273.
  • Ma’aruf, L. M., Garba, M. (2012). “Design and Implementation of an Expert Diet Prescription System”. International Journal of Artificial Intelligence and Expert Systems (IJAE), 3(4), 126-134.
  • Merrell, J., Philpin, S., Warring, J., Hobby, D., Gregory, V. (2012). “Addressing The Nutritional Needs of Older People in Residential Care Homes”. Health & Social Care in the Community, 20(2), 208-215.
  • Merritt, D. (2012). Building Expert Systems in Prolog. Springer Science & Business Media.
  • Metaxiotis, K. S., Samouilidis, J. E. (2000). “Expert Systems in Medicine: Academic Exercise or Practical Tool?”. Journal of Medical Engineering & Technology, 24(2), 68-72.
  • Mustafa, N., Hadi, A., Samsiah, N., Izham, M., Zawawi, A., Ahmad, A. (2020). iDietScore: Meal Recommender System for Athletes and Active Individuals. IJACSA, 11, 12.
  • Nowak, M., Szewczyk, J. (2021). Expert Systems in Medicine. The Book of Articles, 84.
  • Ojokoh, B., Babalola, A. (2016). “A Personalized Healthy Diet Recommender System”. Organization for Women in Science for the Developing World (OWSD), 388-393.
  • Pac, M., Mikutskaya, I., Mulawka, J. (2021). “Knowledge Discovery from Medical Data and Development of an Expert System in Immunology”. Entropy, 23(6), 695.
  • Rajeev, S., Krishnamoorthy, C. S. (1996). Artificial Intelligence and Expert Systems for Engineers. CRC Press.
  • Toledo, R. Y., Alzahrani, A. A., Martinez, L. (2019). “A Food Recommender System Considering Nutritional Information and User Preferences”. IEEE Access, 7, 96695-96711.
  • Turkish Ministry of Health, Directorate General of Public Health (2017). Yeterli ve Dengeli Beslenme Nedir?. https://hsgm.saglik.gov.tr/tr/beslenme/yeterli-ve-dengeli-beslenme-nedir.html. 16.10.2021.
  • van der Merwe A., Kruger H., Steyn T. (2015). “A Diet Expert System Utilizing Linear Programming Models in a Rule-based Inference Engine”. Journal of Applied Operational Research. 7(1):13–22. Whitney, E., Rolfes, S. R. (2018). Understanding Nutrition. Cengage Learning.
Toplam 25 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka
Bölüm Makaleler
Yazarlar

Ceyda Ünal 0000-0002-5503-8124

Cihan Çılgın 0000-0002-8983-118X

Yayımlanma Tarihi 30 Haziran 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 6 Sayı: 1

Kaynak Göster

APA Ünal, C., & Çılgın, C. (2022). Web-Based Expert System Design and Implementation for Personal Nutrition Planning. Uluslararası Yönetim Bilişim Sistemleri Ve Bilgisayar Bilimleri Dergisi, 6(1), 1-12. https://doi.org/10.33461/uybisbbd.1013012