Document Type : Original Article
Authors
1 MSc, Information Technology, Kerman University of Medical Sciences, Kerman, Iran
2 Assistant Professor, Software, Department of Computer Engineering, School of Sciences, Kerman Branch, Islamic Azad University, Kerman, Iran
3 Associate Professor, Medical Informatics, School of Management and Medical Informatics, Kerman University of Medical Sciences, Kerman, Iran
4 Assistant Professor, Nutrition and Public Health, Department of Health Sciences and Nutrition, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran
5 Expert, Nutrition, Kerman University of Medical Sciences, Kerman, Iran
Abstract
Introduction: Pregnancy is one of the most sensitive and important periods of a woman’s life. It is necessary to have a proper diet program based on physiologic changes and individual characteristics during pregnancy in order to meet the needs of mother and fetus, weight control, and prevention of different diseases and complications. The aim of this research was to implement an expert system for weight control surveillance and nutritional consulting.Methods: This study was an applied and descriptive study as performed on a random sample of 100 pregnant women. The system designing was created using expert systems methods based on rules and forward chaining technique. The web-based expert system was designed in two sections: weight controlling and suggestive diet. Then, the system output was compared with the actual advices provided by nutrition experts.Results: Using kappa index in SPSS software, the similarity of the results of designed system to the diagnosis by nutritionist was 0.89 (very strong) in weight control surveillance, and 0.79 (strong) in proposed diet.Conclusion: The findings of the study show that such systems can play an effective helping role in promoting healthy diet, weight control, and using diet among pregnant women, especially those who cannot easily access an expert nutritionist in some areas.
Keywords
- Safari M, Saadatmand N, Azarman M. Food intake pattern and related factors in women referred to medical and health centers of Yasouj-2006. Dena 2007; 2(2): 27-37. [In Persian].
- Mahan LK, Raymond JL. Krause's food & the nutrition care process-e-book. Philadelphia, PA: Elsevier Health Sciences; 2016.
- Shahrokhi Sardou M, Kamyabi Z, Ghahraman M. Clinical midwifery in a comprehensive view. Tehran, Iran: Salem Publications; 2011. [In Persian].
- Ajantha, Singh AK, Malhotra B, Mohan SK, Joshi A. Evaluation of dietary choices, preferences, knowledge and related practices among pregnant women living in an Indian setting. J Clin Diagn Res 2015; 9(8): LC04-LC10.
- Karimy M, Taher M, Fayazi N, Bayati S, Rezaei E, Rahnama F. Beliefs effective on nutritional practices of pregnant women in health centers of Saveh, Iran. J Educ Community Health 2015; 2(3): 28-35. [In Persian].
- Baghianimoghadam M, Sharifi E, Mozafari-Khosravie H, Falahzade H, Karimei-Zarch M. The study of knowledge, attitude and practice of pregnant moders abut consumption of milk and dairy products in Yazd. Toloo e Behdasht 2014; 13(2): 58-71. [In Persian].
- Pakniat H, Movahed F. Relationship between body mass index, weight gain during pregnancy and birth weight of infants. Alborz University Medical Journal 2012; 1(3): 130-6. [In Persian].
- Quinlivan JA, Julania S, Lam L. Antenatal dietary interventions in obese pregnant women to restrict gestational weight gain to Institute of Medicine recommendations: A meta-analysis. Obstet Gynecol 2011; 118(6): 1395-401.
- Gao LL, Larsson M, Luo SY. Internet use by Chinese women seeking pregnancy-related information. Midwifery 2013; 29(7): 730-5.
- Huberty J, Dinkel D, Beets MW, Coleman J. Describing the use of the internet for health, physical activity, and nutrition information in pregnant women. Matern Child Health J 2013; 17(8): 1363-72.
- Sherman LE, Greenfield PM. Forging friendship, soliciting support: A mixed-method examination of message boards for pregnant teens and teen mothers. Comput Human Behav 2013; 29(1): 75-85.
- Storr T, Maher J, Swanepoel E. Online nutrition information for pregnant women: A content analysis. Matern Child Nutr 2017; 13(2).
- Kennedy RA, Mullaney L, Reynolds CM, Cawley S, McCartney DM, Turner MJ. Preferences of women for web-based nutritional information in pregnancy. Public Health 2017; 143: 71-7.
- Durkin J, Durkin J. Expert systems: Design and development. Upper Saddle River, NJ: Prentice Hall; 1998.
- Anggraini RN, Soedjono AR, Sianipar FY, Rochimah S. Infant and pregnancy encyclopedia application. Proceedings of the International Conference on Advanced Mechatronics, Intelligent Manufacture, and. Industrial Automation (ICAMIMIA); 2015 Oct. 15-17; Surabaya, Indonesia.
- Geman O, Chiuchisan I, Iuresi AC, Chiuchisan I, Dimian M, Bosancu A, et al. Intelligent system for a personalized diet of obese patients with cancer. Proceedings of the International Conference and Exposition on Electrical and Power Engineering (EPE); 2014 Oct.16-18; Iasi, Romania.
- Arwan A, Priyambadha B, Sarno R, Sidiq M, Kristianto H. Ontology and semantic matching for diabetic food recommendations. Proceedings of the 5th International Conference on Information Technology and Electrical Engineering; 2013 Oct. 7-8; Yogyakarta, Indonesia.
- Rahmani KH, Abdolahi Z, Minaei M, Torkestani F, Torabi P, Dorosti AR, et al. A comprehensive guide to pregnant and nursing mothers. Tehran, Iran: Andishe-Mandegar Publications; 2013. [In Persian].
- Maher J, Robichaud C, Swanepoel E. Online nutrition information seeking among Australian primigravid women. Midwifery 2018; 58: 37-43.
- Habibpour K, Safari R. Comprehensive SPSS guide to Survey Research (Quantitative Data Analysis). Tehran, Iran: Motefakeran Publications; 2015. [In Persian].
- Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977; 33(1): 159-74.
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