Portfolio item number 1
Short description of portfolio item number 1
Posts by Collection
portfolio
Portfolio item number 2
Short description of portfolio item number 2
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
Paper Title Number 4
Published in GitHub Journal of Bugs, 2024
This paper is about fixing template issue #693.
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3). http://academicpages.github.io/files/paper3.pdf
talks
Interpretable Mortality Simulation and Decision-Making Agent for Heart Transplantation
Published:
Decisions regarding acceptance of a donor’s heart for a patient on the transplant waitlist is currently based on evaluation by a committee of doctors who review many factors but are still quite ad-hoc. Given the volume and range of data collected by the United Network for Organ Sharing (UNOS) on waitlisted patients, donors, clinicians and organs, there is increasing interest among all stakeholders, particularly clinicians, in leveraging model-based approaches that learn from the vast amount of historical data on organ acceptance/rejection to optimize the heart transplantation outcomes and assist human decision making. In response to this need, we benchmark and propose machine learning models to provide accurate and interpretable predictions regarding transplant mortality at both the individual and population levels. The new level of accuracy provides a reliable foundation upon which clinicians can base their decisions with a greater degree of confidence. We have also identified the key features that drive the predictions and verified the clinical significance of these results through close collaboration with the domain experts.
Benchmarking Waitlist Mortality Prediction Through Time-to-Event Modeling using New UNOS Dataset
Published:
Learning from Simulated Patient Trajectories: A Sequential Decision-Making Agent for Heart Transplantation
Published:
Decisions about managing patients on the heart transplant waitlist are currently made by committees of doctors who consider multiple factors, but the process remains largely ad-hoc. With the growing volume of longitudinal patient, donor, and organ data collected by the United Network for Organ Sharing (UNOS) since 2018, there is increasing interest in analytical approaches to support clinical decision-making at the time of organ availability.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.