12 citations · 19 across the 6 of their papers we have counts for
7 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…
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…
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…
Hybrid Self-Attention NEAT: A novel evolutionary approach to improve the NEAT algorithm
Saman Khamesian, Hamed Malek
This article presents a "Hybrid Self-Attention NEAT" method to improve the original NeuroEvolution of Augmenting Topologies (NEAT) algorithm in high-dimensional inputs. Although th…