Karthik K. Tennankore

Orcid: 0000-0002-7919-6709

According to our database1, Karthik K. Tennankore authored at least 11 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2025
Concept-Level Local Explanations of Kidney Transplant Survival Predictions by Black-Box ML Models.
Proceedings of the 2025 18th Health Informatics Knowledge Management Conference, 2025

A Reinforcement Learning Framework for Optimizing Kidney Allocation for Transplant Based on Survival and Ethical Criteria.
Proceedings of the Artificial Intelligence in Medicine - 23rd International Conference, 2025

A Graph Neural Network Approach for Data-Driven Donor-Recipient Matching in Kidney Transplantation.
Proceedings of the Artificial Intelligence in Medicine - 23rd International Conference, 2025

2024
Extracting Decision Paths via Surrogate Modeling for Explainability of Black Box Classifiers.
Proceedings of the 11th IEEE Swiss Conference on Data Science, 2024

2023
Predicting Urgent Dialysis at Ambulance Transport to the Emergency Department Using Machine Learning Methods.
Proceedings of the MEDINFO 2023 - The Future Is Accessible, 2023

Characterizing Cluster-Based Frailty Phenotypes in a Multicenter Prospective Cohort of Kidney Transplant Candidates.
Proceedings of the MEDINFO 2023 - The Future Is Accessible, 2023

Ensemble Clustering to Generate Phenotypes of Kidney Transplant Donors and Recipients.
Proceedings of the MEDINFO 2023 - The Future Is Accessible, 2023

2022
Clinical Guidelines as Executable and Interactive Workflows with FHIR-Compliant Health Data Input Using GLEAN.
Proceedings of the Artificial Intelligence in Medicine, 2022

Explainable Decision Support Using Task Network Models in Notation3: Computerizing Lipid Management Clinical Guidelines as Interactive Task Networks.
Proceedings of the Artificial Intelligence in Medicine, 2022

Extracting Surrogate Decision Trees from Black-Box Models to Explain the Temporal Importance of Clinical Features in Predicting Kidney Graft Survival.
Proceedings of the Artificial Intelligence in Medicine, 2022

2021
Analyzing Association Rules for Graft Failure Following Deceased and Live Donor Kidney Transplantation.
Proceedings of the Public Health and Informatics, 2021


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