Rie Kubota Ando
CoNLL 2006
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).
Rie Kubota Ando
CoNLL 2006
Yi Zhou, Parikshit Ram, et al.
ICLR 2023
Merve Unuvar, Yurdaer Doganata, et al.
CLOUD 2014
Rama Akkiraju, Pinar Keskinocak, et al.
Applied Intelligence