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Therefore, it is important for researchers to examine methods that may encourage the consumer to consider healthier dietary and lifestyle habits as diseases such as obesity, heart disease, and high blood pressure remain a worldwide issue. One promising approach to influencing healthy dietary and lifestyle habits is food recommendation models that recommend food to users based on various factors such as health effects, nutrition, preferences, and daily habits. Unfortunately, much of this work has focused on individual factors such as taste preferences and often neglects to understand other factors that influence our choices. Additionally, the evaluation of technological approaches often lacks user studies in the context of intended use. In this systematic review of food choice technology, we focus on the factors that may influence food choices and how technology can play a role in supporting those choices. We also describe existing work, approaches, trends, and issues in current food choice technology and give advice for future work areas in this space.<\/jats:p>","DOI":"10.1145\/3494580","type":"journal-article","created":{"date-parts":[[2022,3,3]],"date-time":"2022-03-03T19:31:12Z","timestamp":1646335872000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["A Survey on Healthy Food Decision Influences Through Technological Innovations"],"prefix":"10.1145","volume":"3","author":[{"given":"Jermaine","family":"Marshall","sequence":"first","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Lucy Family Institute for Data &amp; Society, University of Notre Dame, Notre Dame, IN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priscilla","family":"Jimenez-Pazmino","sequence":"additional","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Lucy Family Institute for Data &amp; Society, University of Notre Dame, Notre Dame, IN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ronald","family":"Metoyer","sequence":"additional","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Lucy Family Institute for Data &amp; Society, University of Notre Dame, Notre Dame, IN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nitesh V.","family":"Chawla","sequence":"additional","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Lucy Family Institute for Data &amp; Society, University of Notre Dame, Notre Dame, IN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,3,3]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"3197","volume-title":"CHI","author":"Abbar Sofiane","year":"2015","unstructured":"Sofiane Abbar, Yelena Mejova, and Ingmar Weber. 2015. 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