A web-based machine learning nutritionist for people with common diseases (Respiratory, skin pulmonary, cadiovascular diseases).

Fernando, Afer John R. and Manoy, Carlo R. and Pilapil, Jessica G. (2013) A web-based machine learning nutritionist for people with common diseases (Respiratory, skin pulmonary, cadiovascular diseases). Undergraduate thesis, De La Salle University-Dasmarinas.

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Abstract

The Web- Based Machine Learning Nutritionist for People with Common Diseases is an online expert system that guides people in monitoring food diet and proper food intake when users have diseases. This system includes: vitamins and minerals, diseases given by the proponents and list of nutritional foods, wherein people can see the list of foods that are allowed and not allowed for their illnesses. The mentioned foods contain vitamins and minerals that can help lessen the sickness of a person. The processing of the inputs will be done in a real time system, thus, a lot of effort and time will be saved. It keeps a database of the patient thus providing the user with patients‟ records and history. To make the system much more reliable and true, the proponents conducted interviews with several experts in the field of nutrition. The gathered data from the experts is used as the basis of the system‟s knowledge base on giving proper vitamin intake at every disease. Unlike conventional programming, developing an expert system is a highly iterative process which requires up to date knowledge base. ASP.Net is the primary language used by the proponents in programming the proposed system. It was developed by Microsoft and it is a simple, modern, general-purpose, object-oriented programming language. The proponents used Visual Studio 2010 as the programming platform of ASP.Net to create a friendly user interface, database and JavaScript for generating patients‟ reports.

Item Type: Thesis (Undergraduate)
Additional Information: CS 1149 2013
Keywords: Web-based Machine.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
Depositing User: Ms. Bibiana Alcantara
Date Deposited: 11 Jan 2016 05:06
Last Modified: 11 Jan 2016 05:06
URI: http://thesis.dlsud.edu.ph/id/eprint/596

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