About
Biography
I am a computational researcher aiming to develop technologies to translate and transform pediatric clinical care using machine learning. My foundational training is in economics and statistics. I strive to improve the efficiency and impact of health interventions by getting more out of the information already collected through standards of care.
My work primarily focuses on extracting more information from biomedical imaging data, with the goal of enabling faster and easier interpretation by a larger share of clinicians, such as novices and those who don’t specialize in pediatrics.
I have already developed models for prediction in hydronephrosis ultrasound, pediatric echocardiography, hepatocellular carcinoma recurrence, irritable bowel disease (IBD) diagnosis and drug response, and the diagnosis of motile ciliopathy. I have been a researcher for over 10 years and began working at Cincinnati Children’s in 2023.
Research Areas
Publications
Validation of the Toronto recurrence inference using machine-learning for post-transplant hepatocellular carcinoma model. Communications Medicine. 2025; 5:284.
Peripheral blood DNA methylation predicts the early onset of primary tumor in TP53 mutation carriers. Nature Communications. 2025; 16:7976.
Longitudinal image-based prediction of surgical intervention in infants with hydronephrosis using deep learning: Is a single ultrasound enough?. PLOS Digital Health. 2025; 4:e0000939.
Reply by Authors. The Journal of Urology. 2025; 214:88-89.
Machine Learning Analysis of Videourodynamics to Predict Incident Hydronephrosis in Patients With Spina Bifida. The Journal of Urology. 2025; 214:80-89.
A living scoping review and online repository of artificial intelligence models in pediatric urology: Results from the AI-PEDURO collaborative. Journal of Pediatric Urology. 2025; 21:765-772.
CHARACTERIZING SLE PATIENTS INTO TYPE 1 AND TYPE 2 DISEASE STATES: INSIGHTS FROM A SINGLE LUPUS COHORT. The Journal of rheumatology. 2025; 52:210-211.
AI-PEDURO - Artificial intelligence in pediatric urology: Protocol for a living scoping review and online repository. Journal of Pediatric Urology. 2025; 21:532-538.
iModEst: disentangling -omic impacts on gene expression variation across genes and tissues. NAR Genomics and Bioinformatics. 2025; 7:lqaf011.
CANAIRI: the Collaboration for Translational Artificial Intelligence Trials in healthcare. Nature Medicine. 2025; 31:9-11.
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