Sashi Novitasari, Takashi Fukuda, et al.
INTERSPEECH 2025
Abdominal imaging is a crucial tool in treatment planning for patients with kidney tumors. Prior research has robustly demonstrated the relationship between tumor morphology and important oncologic outcomes such as stage, grade, and survival. Increasingly, abdominal imaging is being recognized as a rich source of information about the patient's overall health status as well, which could provide important complementary information to oncologic predictions in treatment decisions. In this work, we present Age Discrepancy, a novel and intuitive variable that can be used to quantify the frailty of kidney tumor patients on the basis of their abdominal image, either through an AI-based computer vision approach, or through manual expert assessment. This new variable could be used to more effectively stratify kidney tumor patients on the basis of perioperative risk when used in conjunction with existing measures such as the patient's chronological age and their Charlson Comorbidity Index (CCI).
Sashi Novitasari, Takashi Fukuda, et al.
INTERSPEECH 2025
Shachar Don-Yehiya, Leshem Choshen, et al.
ACL 2025
Seung Gu Kang, Jeff Weber, et al.
ACS Fall 2023
Dzung Phan, Vinicius Lima
INFORMS 2023