2 citations · 3 across the 11 of their papers we have counts for
12 papers
INCONVENIENT: A Benchmark to Assess LLM Generalization Capabilities from Convenience Samples
Sara Rezaeimanesh, Chad Klochko, Kundan Thind +1
Machine learning models for tabular prediction typically assume that training data are representative of the population on which they will be deployed. In practice, however, data a…
What Language Models Know But Don't Say: Non-Generative Prior Extraction for Generalization
Sara Rezaeimanesh, Kundan Thind, Farzan Siddiqui +1
In domains like medicine and finance, large-scale labeled data is costly and often unavailable, leading to models trained on small datasets that struggle to generalize to real-worl…
Extracting Overlapping Microservices from Monolithic Code via Deep Semantic Embeddings and Graph Neural Network-Based Soft Clustering
Morteza Ziabakhsh, Kiyan Rezaee, Sadegh Eskandari +2
Modern software systems are increasingly shifting from monolithic architectures to microservices to enhance scalability, maintainability, and deployment flexibility. Existing micro…
MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks
Lotfi Abdelkrim Mecharbat, Alberto Marchisio, Muhammad Shafique +2
There has been a surge in optimizing edge Deep Neural Networks (DNNs) for accuracy and efficiency using traditional optimization techniques such as pruning, and more recently, empl…
Online Continual Learning: A Systematic Literature Review of Approaches, Challenges, and Benchmarks
Seyed Amir Bidaki, Amir Mohammadkhah, Kiyan Rezaee +4
Online Continual Learning (OCL) is a critical area in machine learning, focusing on enabling models to adapt to evolving data streams in real-time while addressing challenges such…
GLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image Segmentation
Niloufar Eghbali, Hassan Bagher-Ebadian, Tuka Alhanai +1
Vision Transformers (ViTs) have shown promise in medical image semantic segmentation (MISS) by capturing long-range correlations. However, ViTs often struggle to model local spatia…
Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework
Niloufar Eghbali, Tuka Alhanai, Mohammad M. Ghassemi
Mechanical Ventilation (MV) is a critical life-support intervention in intensive care units (ICUs). However, optimal ventilator settings are challenging to determine because of the…
Machine-arranged Interactions Improve Institutional Belonging and Cohesion
Mohammad M. Ghassemi, Tuka Alhanai
We investigated how participation in machine-arranged meetings were associated with feelings of institutional belonging and perceptions of demographic groups. We collected data fro…
An LSTM Feature Imitation Network for Hand Movement Recognition from sEMG Signals
Chuheng Wu, S. Farokh Atashzar, Mohammad M. Ghassemi +1
Surface Electromyography (sEMG) is a non-invasive signal that is used in the recognition of hand movement patterns, the diagnosis of diseases, and the robust control of prostheses.…
Iterative Prompt Refinement for Radiation Oncology Symptom Extraction Using Teacher-Student Large Language Models
Reza Khanmohammadi, Ahmed I Ghanem, Kyle Verdecchia +7
This study introduces a novel teacher-student architecture utilizing Large Language Models (LLMs) to improve prostate cancer radiotherapy symptom extraction from clinical notes. Mi…
The Influence of Biomedical Research on Future Business Funding: Analyzing Scientific Impact and Content in Industrial Investments
Reza Khanmohammadi, Simerjot Kaur, Charese H. Smiley +4
This paper investigates the relationship between scientific innovation in biomedical sciences and its impact on industrial activities, focusing on how the historical impact and con…
An Introduction to Natural Language Processing Techniques and Framework for Clinical Implementation in Radiation Oncology
Reza Khanmohammadi, Mohammad M. Ghassemi, Kyle Verdecchia +8
Natural Language Processing (NLP) is a key technique for developing Medical Artificial Intelligence (AI) systems that leverage Electronic Health Record (EHR) data to build diagnost…