Literature DB >> 9739801

An artificial intelligence system for computer-assisted menu planning.

G J Petot1, C Marling, L Sterling.   

Abstract

Planning nutritious and appetizing menus is a complex task that researchers have tried to computerize since the early 1960s. We have attempted to facilitate computer-assisted menu planning by modeling the reasoning an expert dietitian uses to plan menus. Two independent expert systems were built, each designed to plan a daily menu meeting the nutrition needs and personal preferences of an individual client. One system modeled rule-based, or logical, reasoning, whereas the other modeled case-based, or experiential, reasoning. The 2 systems were evaluated and their strengths and weaknesses identified. A hybrid system was built, combining the best of both systems. The hybrid system represents an important step forward because it plans daily menus in accordance with a person's needs and preferences; the Reference Daily Intakes; the Dietary Guidelines for Americans; and accepted aesthetic standards for color, texture, temperature, taste, and variety. Additional work to expand the system's scope and to enhance the user interface will be needed to make it a practical tool. Our system framework could be applied to special-purpose menu planning for patients in medical settings or adapted for institutional use. We conclude that an artificial intelligence approach has practical use for computer-assisted menu planning.

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Year:  1998        PMID: 9739801     DOI: 10.1016/S0002-8223(98)00231-4

Source DB:  PubMed          Journal:  J Am Diet Assoc        ISSN: 0002-8223


  3 in total

1.  Definition of information technology architectures for continuous data management and medical device integration in diabetes.

Authors:  M Elena Hernando; Mario Pascual; Carlos H Salvador; Gema García-Sáez; Agustín Rodríguez-Herrero; Iñaki Martínez-Sarriegui; Enrique J Gómez
Journal:  J Diabetes Sci Technol       Date:  2008-09

2.  NutriSonic web expert system for meal management and nutrition counseling with nutrient time-series analysis, e-food exchange and easy data transition.

Authors:  Soon-Myung Hong; Jee-Ye Cho; Jin-Hee Lee; Gon Kim; Min-Chan Kim
Journal:  Nutr Res Pract       Date:  2008-06-30       Impact factor: 1.926

3.  DietPal: a Web-based dietary menu-generating and management system.

Authors:  Shahrul A Noah; Siti Norulhuda Abdullah; Suzana Shahar; Helmi Abdul-Hamid; Nurkahirizan Khairudin; Mohamed Yusoff; Rafidah Ghazali; Nooraini Mohd-Yusoff; Nik Shanita Shafii; Zaharah Abdul-Manaf
Journal:  J Med Internet Res       Date:  2004-01-30       Impact factor: 5.428

  3 in total

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