Abstract
Kidney cancer is a global health concern, and accurate assessment of patient frailty is crucial for optimizing surgical outcomes. This paper introduces AI Age Discrepancy, a novel metric derived from machine learning analysis of preoperative abdominal CT scans, as a potential indicator of frailty and postoperative risk in kidney cancer patients. This retrospective study of 599 patients from the 2023 Kidney Tumor Segmentation (KiTS) challenge dataset found that a higher AI Age Discrepancy is significantly associated with longer hospital stays and lower overall survival rates, independent of established factors. This suggests that AI Age Discrepancy may provide valuable insights into patient frailty and could thus inform clinical decision-making in kidney cancer treatment.
Original language | English (US) |
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Title of host publication | Cancer Prevention, Detection, and Intervention - 3rd MICCAI Workshop, CaPTion 2024, Held in Conjunction with MICCAI 2024, Proceedings |
Editors | Sharib Ali, Fons van der Sommen, Iris Kolenbrander, Bartłomiej Władysław Papież, Noha Ghatwary, Yueming Jin |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 167-175 |
Number of pages | 9 |
ISBN (Print) | 9783031733758 |
DOIs | |
State | Published - 2025 |
Event | 3rd International Workshop on Cancer Prevention, detection and intervenTion, CaPTion 2024, held in Conjunction with 27th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024 - Marrakesh, Morocco Duration: Oct 6 2024 → Oct 6 2024 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 15199 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 3rd International Workshop on Cancer Prevention, detection and intervenTion, CaPTion 2024, held in Conjunction with 27th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024 |
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Country/Territory | Morocco |
City | Marrakesh |
Period | 10/6/24 → 10/6/24 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Keywords
- Frailty
- Kidney Cancer
- Machine Learning