ID
11
Pathway
Clinical Care
Description
The project aims to evaluate the feasibility of combining AI deep learning and conventional computer vision techniques to classify kidney ultrasound images for the presence or absence of chronic kidney disease. This project is under the larger project of “Radiology Residency Global Outreach Program Survey”, where findings from this field study are applied to the current project in terms of expansion and global outreach.
Goals
Perform a retrospective analysis of around 1000 patient cases in order to establish a 10-year longitudinal database of patients with chronic kidney disease (CKD).
Develop and validate multimodal artificial intelligence models for CKD evaluation, risk stratification, and prediction of clinically meaningful outcomes
Improve diagnostic capabilities in resource-limited clinical settings.
Develop and validate multimodal artificial intelligence models for CKD evaluation, risk stratification, and prediction of clinically meaningful outcomes
Improve diagnostic capabilities in resource-limited clinical settings.
Mentor
Young Kim
Mentor E-mail
Young.Kim@umassmemorial.org
Department
Radiology
Prior Students
Class of 2029:
Clara Baek (clara.baek@umassmed.edu)
Class of 2027:
Shabaz Khan
Xin Song
Cristina Hayes
Clara Baek (clara.baek@umassmed.edu)
Class of 2027:
Shabaz Khan
Xin Song
Cristina Hayes
Availability
Yes
Number Spots
2