Multi-Organ Exchange
Authors: John P. Dickerson, Tuomas Sandholm
JAIR 2017 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We support this result experimentally on demographically accurate multi-organ exchanges. |
| Researcher Affiliation | Academia | John P. Dickerson EMAIL Department of Computer Science University of Maryland College Park, MD 20742 USA Tuomas Sandholm EMAIL Computer Science Department Carnegie Mellon University Pittsburgh, PA 15213 USA |
| Pseudocode | Yes | Algorithm 1: Compatibility graph generator |
| Open Source Code | No | The paper does not explicitly state that the code for the described methodology is open-source, nor does it provide a link to a code repository. It mentions 'Our solver that is used by UNOS' but not its public availability. |
| Open Datasets | Yes | We draw candidate genders from the OPTN data set, and donor genders from the greater US population through the 2010 US Census report... We sample ages (dependent on gender) for candidates from the OPTN pool and for the donors from the 2010 US Census at a granularity level of one year... we sample from a fine-grained table of weights recently released by the Center for Disease Control (Mc Dowell, Fryar, Ogden, & Flegal, 2008). |
| Dataset Splits | No | The paper describes generating compatibility graphs and simulating dynamic scenarios where candidates enter and exit a pool over time. It does not provide traditional training/test/validation dataset splits used for model evaluation. |
| Hardware Specification | No | This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number OCI-1053575; specifically, it used the Blacklight system at the Pittsburgh Supercomputing Center (PSC). While XSEDE and Blacklight are mentioned, no specific hardware details like CPU/GPU models or memory are provided. |
| Software Dependencies | No | The paper mentions algorithmic methods like "integer programming" and the "branch-and-price framework" and refers to "Our solver that is used by UNOS", but it does not specify any particular software (e.g., CPLEX, Gurobi) or their version numbers. |
| Experiment Setup | Yes | We start with a pool of |V| = 400 pairs... a post-match, pre-transplant failure probability is drawn from real data, as motivated by Dickerson et al. (2018)... In expectation |Vnew| = 233 new candidates arrive in the pool per month, and the algorithm continues. We test over 24 months... exogeneous incompatibility rate f {0.5, 0.7, 0.9}... We set p K L = 0.5... include 100 altruistic kidney donors who enter the combined pool at an expected constant rate. |