Category: Publications
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P93 Precision Behavioral Nutrition: Development of the NutriPCP Inference Engine for Data-driven Diet Goals in Primary Care
Click here to read the full paper! Objective: To develop a computational system that uses dietary recall data to prioritize behavioral goals to facilitate efficient, personalized collaborative goal-setting in primary care. Use of Theory or Research: The Chronic Care Model posits that synergy between the healthcare system and patient self-management will improve chronic disease outcomes.…
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Optimal App Use by Dietitians Limited by Payment Structures, App Usability, and Lack of Dietitian Familiarity With Available Apps: A Qualitative Thematic Analysis
Read the full publication here! Objectives: To expand on previous survey-based research that provided a basic understanding of dietitian perspectives on app use by exploring factors that are influencing dietitian decision-making regarding the use and recommendation of apps with individual clients. Methods: 20–60-minute semi-structured interviews conducted in-person, over the phone, or via videoconferencing from November…
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From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations
Read the full paper on ACM Digital Library! |Abstract| Self-tracking can help personalize self-management interventions for chronic conditions like type 2 diabetes (T2D), but reflecting on personal data requires motivation and literacy. Machine learning (ML) methods can identify patterns, but a key challenge is making actionable suggestions based on personal health data. We introduce GlucoGoalie,…