12月25日的OPOM应用程序分析
OPOM
- Interpretable AI LLC
- Apple 应用商店
- 免费
- 医疗
The successful clinical application of liver transplantation has generated a discrepancy between supply and demand, thereby generating a persistent insufficient organ supply that results in thousands of candidate deaths every year while candidates await liver transplantation.
Given the scarcity of this resource, the Model for End-Stage Liver Disease (MELD) accurately prioritizes a waitlisted candidate’s likelihood of death within the near future, so that the limited supply of donated livers can be allocated to maximize the benefit from transplantation. The MELD score was updated in 2014 and 2015.
The objective of OPOM is to improve the accuracy of the MELD method and include hepatocellular carcinoma (HCC) patients, and then demonstrate effectiveness with simulation.
The first order requirement to implement an allocation methodology is to achieve alignment on methodology. This methodology aims to determine the probability that a patient will either die or become unsuitable for liver transplantation within three months, given his or her individual characteristics, and then allocate the limited supply of donated livers to the patients that need it and then maximize benefit of transplantation
Interpretability and transparency of the underlying processes is required to achieve alignment.
Based on the work by D. Bertsimas, J. Kung, N. Trichakis, Y. Wang, R. Hirose and P. Vagefi https://doi.org/10.1111/ajt.15172
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十二月 25, 2025