1 citations · 1 across the 2 of their papers we have counts for
4 papers
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…
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…