12 citations · 38 across the 12 of their papers we have counts for
12 papers
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…
Counterfactual Modeling with Fine-Tuned LLMs for Health Intervention Design and Sensor Data Augmentation
Shovito Barua Soumma, Asiful Arefeen, Stephanie M. Carpenter +2
Counterfactual explanations (CFEs) provide human-centric interpretability by identifying the minimal, actionable changes required to alter a machine learning model's prediction. Th…
RealAC: A Domain-Agnostic Framework for Realistic and Actionable Counterfactual Explanations
Asiful Arefeen, Shovito Barua Soumma, Hassan Ghasemzadeh
Counterfactual explanations provide human-understandable reasoning for AI-made decisions by describing minimal changes to input features that would alter a model's prediction. To b…
SenseCF: LLM-Prompted Counterfactuals for Intervention and Sensor Data Augmentation
Shovito Barua Soumma, Asiful Arefeen, Stephanie M. Carpenter +2
Counterfactual explanations (CFs) offer human-centric insights into machine learning predictions by highlighting minimal changes required to alter an outcome. Therefore, CFs can be…
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…
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…
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…
Inter-Beat Interval Estimation with Tiramisu Model: A Novel Approach with Reduced Error
Asiful Arefeen, Ali Akbari, Seyed Iman Mirzadeh +3
Inter-beat interval (IBI) measurement enables estimation of heart-rate variability (HRV) which, in turns, can provide early indication of potential cardiovascular diseases. However…