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Meal Suggestions for Caregivers and Indecisive Individuals Without a Set Food Plan

dc.contributor.authorCunha, Carlos
dc.contributor.authorCardoso, Tiago R.
dc.contributor.authorP. Duarte, Rui
dc.date.accessioned2024-05-27T11:18:19Z
dc.date.available2024-05-27T11:18:19Z
dc.date.issued2024
dc.description.abstractRecommendation systems have played a crucial role in assisting users with decision-making across various domains. In nutrition, these systems can provide valuable assistance by offering alternatives to inflexible food plans that often result in abandonment due to personal food preferences or the temporary unavailability of certain ingredients. Moreover, they can aid caregivers in selecting the most suitable food options for dependent individuals based on their specific daily goals. In this article, we develop a data-driven model using a multilayer perceptron (MLP) network to assist individuals in making informed meal choices that align with their preferences and daily goals. Our study focuses on predicting complete meals rather than solely on predicting individual food items since food choices are often influenced by specific combinations of ingredients that work harmoniously together. Based on our evaluation of a comprehensive dataset, the results of our study demonstrate that the model achieves a prediction accuracy of over 60% for an individual complete meal.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCunha, C.A.S., Cardoso, T.R., Duarte, R.P. (2024). Meal Suggestions for Caregivers and Indecisive Individuals Without a Set Food Plan. In: Coelho, P.J., Pires, I.M., Lopes, N.V. (eds) Smart Objects and Technologies for Social Good. GOODTECHS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 556. Springer, Cham. https://doi.org/10.1007/978-3-031-52524-7_13pt_PT
dc.identifier.doi10.1007/978-3-031-52524-7_13pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.19/8405
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationNational Funds fund this work through the FCT—Foundation for Science and Technology, I.P., within the scope of the project Ref. UIDB/05583/2020. Furthermore, we thank the Research Centre in Digital Services (CISeD), under project Ref. PIDI/CISeD/2022/009, and the Polytechnic of Viseu for their support.pt_PT
dc.subjectFood recommendationpt_PT
dc.subjectDeep learningpt_PT
dc.subjectAutonomous nutritionpt_PT
dc.titleMeal Suggestions for Caregivers and Indecisive Individuals Without a Set Food Planpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage183pt_PT
oaire.citation.startPage172pt_PT
oaire.citation.titleSmart Objects and Technologies for Social Good. GOODTECHS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 556pt_PT
oaire.citation.volume556pt_PT
person.familyNameCunha
person.familyNameMonteiro Amaro Duarte
person.givenNameCarlos
person.givenNameRui Pedro
person.identifier2081924
person.identifiergIYE8M4AAAAJ
person.identifier.ciencia-idD71F-FC65-1F07
person.identifier.ciencia-id211F-55A0-4B63
person.identifier.orcid0000-0002-2754-5401
person.identifier.orcid0000-0002-6819-0985
person.identifier.scopus-author-id39361170900
person.identifier.scopus-author-id14059938600
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication384f50cd-9e87-40bd-b610-58008e05bec1
relation.isAuthorOfPublicationd56c3162-80a4-4ade-810d-43bae4ee6d73
relation.isAuthorOfPublication.latestForDiscovery384f50cd-9e87-40bd-b610-58008e05bec1

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