Syed Hasib Akhter Faruqui

Assistant Professor

Sam Houston State University

United States

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About

Syed Hasib Akhter Faruqui is an Assistant Professor at Sam Houston State University in the United States. His research areas encompass machine learning applications in medical imaging, predictive modeling of chronic conditions, and advanced graph neural networks. Recent articles include studies on eye-tracking technology for radiologists and the development of algorithms for understanding complex patterns in healthcare data.

Articles (10)

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2025

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2025

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2024

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2024

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2024

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2024

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2021

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2021

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2021

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2020

Collaborators (3)

Joseph McCormick

James H. Steele Professor

UNITED STATES

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Mary Jo Pugh

Professor

University of Utah

UNITED STATES

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peyman najafirad

Associate Professor

University of Texas at San Antonio

UNITED STATES

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Syed Hasib Akhter Faruqui

Research Interests

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About

Articles (10)

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

Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study

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

A Laplacian regularized graph neural network for predictive modeling of multiple chronic conditions

Background Subtraction Angiography with Deep Learning Using Multi-frame Spatiotemporal Angiographic Input

Evaluating outcome associations with race after mechanical thrombectomy: an analysis of the NVQI-QOD acute ischemic stroke registry

Dynamic Functional Continuous Time Bayesian Networks for Prediction and Monitoring of the Impact of Patients’ Modifiable Lifestyle Behaviors on the Emergence of Multiple Chronic Conditions

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

Dynamic Functional Continuous Time Bayesian Networks for Prediction and Monitoring of the Impact of Patients’ Modifiable Lifestyle Behaviors on the Emergence of Multiple Chronic Conditions

Summarizing Complex Graphical Models of Multiple Chronic Conditions Using the Second Eigenvalue of Graph Laplacian: Algorithm Development and Validation

Collaborators (3)

Joseph McCormick

Mary Jo Pugh

peyman najafirad

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