12 citations · 34 across the 12 of their papers we have counts for
13 papers
Peer-Grounded Counterfactual Path Planning for Chronic Health Management
Saman Khamesian, Hassan Ghasemzadeh
Effective behavioral intervention in chronic disease management requires not a single prescription but a sequence of incremental steps, each grounded in what real, similar individu…
MetaPlate: Counterfactual-Guided RAG-LLM Tool for Personalized Food Recommendation and Hyperglycemia Prevention
Asiful Arefeen, Carol Johnston, Hassan Ghasemzadeh
Postprandial hyperglycemia is a key risk factor for metabolic disorders; however, existing dietary guidance is often static, impractical, and insufficiently personalized, providing…
GUIDE: Reinforcement Learning for Behavioral Action Support in Type 1 Diabetes
Saman Khamesian, Sri Harini Balaji, Di Yang Shi +5
Type 1 diabetes (T1D) management requires continuous adjustment of insulin and lifestyle behaviors to maintain blood glucose within a safe target range. Although automated insulin…
AZT1D: A Real-World Dataset for Type 1 Diabetes
Saman Khamesian, Asiful Arefeen, Bithika M. Thompson +2
High quality real world datasets are essential for advancing data driven approaches in type 1 diabetes (T1D) management, including personalized therapy design, digital twin systems…
GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals
Asiful Arefeen, Saman Khamesian, Maria Adela Grando +2
Frequent and long-term exposure to hyperglycemia increases the risk of chronic complications, including neuropathy, nephropathy, and cardiovascular disease. Existing continuous sub…
AIMI: Leveraging Future Knowledge and Personalization in Sparse Event Forecasting for Treatment Adherence
Abdullah Mamun, Diane J. Cook, Hassan Ghasemzadeh
Adherence to prescribed treatments is crucial for individuals with chronic conditions to avoid costly or adverse health outcomes. For certain patient groups, intensive lifestyle in…
MealMeter: Using Multimodal Sensing and Machine Learning for Automatically Estimating Nutrition Intake
Asiful Arefeen, Samantha Fessler, Sayyed Mostafa Mostafavi +2
Accurate estimation of meal macronutrient composition is a pre-perquisite for precision nutrition, metabolic health monitoring, and glycemic management. Traditional dietary assessm…
LLM-Powered Prediction of Hyperglycemia and Discovery of Behavioral Treatment Pathways from Wearables and Diet
Abdullah Mamun, Asiful Arefeen, Susan B. Racette +4
Postprandial hyperglycemia, marked by the blood glucose level exceeding the normal range after consuming a meal, is a critical indicator of progression toward type 2 diabetes in pe…
NutriGen: Personalized Meal Plan Generator Leveraging Large Language Models to Enhance Dietary and Nutritional Adherence
Saman Khamesian, Asiful Arefeen, Stephanie M. Carpenter +1
Maintaining a balanced diet is essential for overall health, yet many individuals struggle with meal planning due to nutritional complexity, time constraints, and lack of dietary k…
Glycemic-Aware and Architecture-Agnostic Training Framework for Blood Glucose Forecasting in Type 1 Diabetes
Saman Khamesian, Asiful Arefeen, Maria Adela Grando +2
Managing Type 1 Diabetes (T1D) demands constant vigilance as individuals strive to regulate their blood glucose levels and avoid dysglycemia, including hyperglycemia and hypoglycem…
Multimodal Physical Activity Forecasting in Free-Living Clinical Settings: Hunting Opportunities for Just-in-Time Interventions
Abdullah Mamun, Krista S. Leonard, Megan E. Petrov +2
Objective: This research aims to develop a lifestyle intervention system, called MoveSense, that forecasts a patient's activity behavior to allow for early and personalized interve…
Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health
Abdullah Mamun, Lawrence D. Devoe, Mark I. Evans +3
Early detection of intrapartum risks enables timely interventions to prevent or mitigate adverse labor outcomes such as cerebral palsy. However, accurate automated systems to suppo…
Designing User-Centric Behavioral Interventions to Prevent Dysglycemia with Novel Counterfactual Explanations
Asiful Arefeen, Hassan Ghasemzadeh
Monitoring unexpected health events and taking actionable measures to avert them beforehand is central to maintaining health and preventing disease. Therefore, a tool capable of pr…