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1. Optimal Kidney Exchange with Immunosuppressants

   Aziz, Haris; Cseh, Agnes; Dickerson, John P; McElfresh, Duncan C (April 2021, Proceedings of the AAAI Conference on Artificial Intelligence)

   Algorithms for exchange of kidneys is one of the key successful applications in market design, artificial intelligence, and operations research. Potent immunosuppressant drugs suppress the body's ability to reject a transplanted organ up to the point that a transplant across blood- or tissue-type incompatibility becomes possible. In contrast to the standard kidney exchange problem, we consider a setting that also involves the decision about which recipients receive from the limited supply of immunosuppressants that make them compatible with originally incompatible kidneys. We firstly present a general computational framework to model this problem. Our main contribution is a range of efficient algorithms that provide flexibility in terms of meeting meaningful objectives. Motivated by the current reality of kidney exchanges using sophisticated mathematical-programming-based clearing algorithms, we then present a general but scalable approach to optimal clearing with immunosuppression; we validate our approach on realistic data from a large fielded exchange. 

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2. Mutual Learning Algorithm for Kidney Cyst, Kidney Tumor, and Kidney Stone Diagnosis.

   https://doi.org/10.15439/2023F378  

   Chowdhury, S.T.; Mukhopadhyay, S; Narendra, K. (November 2023, Proceedings of the 18th Conference on Computer Science and Intelligence Systems)
3. Kidney Exchange with Inhomogeneous Edge Existence Uncertainty

   Bidkhori, Hoda; Dickerson, John; McElfresh, Duncan; Ren, Ke (April 2020, Uncertainty in artificial intelligence)

   null (Ed.)
4. Kidney-Targeted Redox Scavenger Therapy Prevents Cisplatin-Induced Acute Kidney Injury

   https://doi.org/10.3389/fphar.2021.790913  

   Williams, Ryan M; Shah, Janki; Mercer, Elizabeth; Tian, Helen S; Thompson, Vanessa; Cheung, Justin M; Dorso, Madeline; Kubala, Jaclyn M; Gudas, Lorraine J; de_Stanchina, Elisa; et al (January 2022, Frontiers in Pharmacology)

   Cisplatin-induced acute kidney injury (CI-AKI) is a significant co-morbidity of chemotherapeutic regimens. While this condition is associated with substantially lower survival and increased economic burden, there is no pharmacological agent to effectively treat CI-AKI. The disease is hallmarked by acute tubular necrosis of the proximal tubular epithelial cells primarily due to increased oxidative stress. We investigated a drug delivery strategy to improve the pharmacokinetics of an approved therapy that does not normally demonstrate appreciable efficacy in CI-AKI, as a preventive intervention. In prior work, we developed a kidney-selective mesoscale nanoparticle (MNP) that targets the renal proximal tubular epithelium. Here, we found that the nanoparticles target the kidneys in a mouse model of CI-AKI with significant damage. We evaluated MNPs loaded with the reactive oxygen species scavenger edaravone, currently used to treat stroke and ALS. We found a marked and significant therapeutic benefit with edaravone-loaded MNPs, including improved renal function, which we demonstrated was likely due to a decrease in tubular epithelial cell damage and death imparted by the specific delivery of edaravone. The results suggest that renal-selective edaravone delivery holds potential for the prevention of acute kidney injury among patients undergoing cisplatin-based chemotherapy. 

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5. Failure-Aware Kidney Exchange

   https://doi.org/10.1287/mnsc.2018.3026  

   Dickerson, John P.; Procaccia, Ariel D.; Sandholm, Tuomas (July 2018, Management Science)