activity
20202024
most citedA Model Predictive Control Functional Continuous Time Bayesian Network for Self-Management of Multiple Chronic Conditions

3 citations · 5 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2024★ 1 cited

A Generative Framework for Predictive Modeling of Multiple Chronic Conditions Using Graph Variational Autoencoder and Bandit-Optimized Graph Neural Network

Julian Carvajal Rico, Adel Alaeddini, Syed Hasib Akhter Faruqui +2

Predicting the emergence of multiple chronic conditions (MCC) is crucial for early intervention and personalized healthcare, as MCC significantly impacts patient outcomes and healt…

cs.LG2024

Nurse-in-the-Loop Artificial Intelligence for Precision Management of Type 2 Diabetes in a Clinical Trial Utilizing Transfer-Learned Predictive Digital Twin

Syed Hasib Akhter Faruqui, Adel Alaeddini, Yan Du +3

Background: Type 2 diabetes (T2D) is a prevalent chronic disease with a significant risk of serious health complications and negative impacts on the quality of life. Given the impa…

cs.HC2023

Incorporation of Eye-Tracking and Gaze Feedback to Characterize and Improve Radiologist Search Patterns of Chest X-rays: A Randomized Controlled Clinical Trial

Carolina Ramirez-Tamayo, Syed Hasib Akhter Faruqui, Stanford Martinez +6

Diagnostic errors in radiology often occur due to incomplete visual assessments by radiologists, despite their knowledge of predicting disease classes. This insufficiency is possib…

cs.CV2023

Discrimination of Radiologists Utilizing Eye-Tracking Technology and Machine Learning: A Case Study

Stanford Martinez, Carolina Ramirez-Tamayo, Syed Hasib Akhter Faruqui +7

Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate this problem, radiologists employ personalized and high-dimensional visual search strategies,…

cs.LG2023★ 1 cited

Machine learning tools to improve nonlinear modeling parameters of RC columns

Hamid Khodadadi Koodiani, Elahe Jafari, Arsalan Majlesi +3

Modeling parameters are essential to the fidelity of nonlinear models of concrete structures subjected to earthquake ground motions, especially when simulating seismic events stron…

cs.LG2022★ 3 cited

A Model Predictive Control Functional Continuous Time Bayesian Network for Self-Management of Multiple Chronic Conditions

Syed Hasib Akhter Faruqui, Adel Alaeddini, Jing Wang +3

Multiple chronic conditions (MCC) are one of the biggest challenges of modern times. The evolution of MCC follows a complex stochastic process that is influenced by a variety of ri…

stat.ME2021

Nonlinear State Space Modeling and Control of the Impact of Patients' Modifiable Lifestyle Behaviors on the Emergence of Multiple Chronic Conditions

Syed Hasib Akhter Faruqui, Adel Alaeddini, Jing Wang +2

The emergence and progression of multiple chronic conditions (MCC) over time often form a dynamic network that depends on patient's modifiable risk factors and their interaction wi…

cs.LG2020

A Functional Model for Structure Learning and Parameter Estimation in Continuous Time Bayesian Network: An Application in Identifying Patterns of Multiple Chronic Conditions

Syed Hasib Akhter Faruqui, Adel Alaeddini, Jing Wang +1

Bayesian networks are powerful statistical models to study the probabilistic relationships among set random variables with major applications in disease modeling and prediction. He…