3 citations · 7 across the 9 of their papers we have counts for
5 papers · 1 filter
Glucodensity Functional Profiles Outperform Traditional Continuous Glucose Monitoring Metrics
Marcos Matabuena, Rahul Ghosal, Javier Enrique Aguilar +6
Continuous glucose monitoring (CGM) data has revolutionized the management of type 1 diabetes, particularly when integrated with insulin pumps to mitigate clinical events such as h…
Functional Time Transformation Model with Applications to Digital Health
Rahul Ghosal, Marcos Matabuena, Sujit K. Ghosh
The advent of wearable and sensor technologies now leads to functional predictors which are intrinsically infinite dimensional. While the existing approaches for functional data an…
Conformal uncertainty quantification using kernel depth measures in separable Hilbert spaces
Marcos Matabuena, Rahul Ghosal, Pavlo Mozharovskyi +2
Depth measures have gained popularity in the statistical literature for defining level sets in complex data structures like multivariate data, functional data, and graphs. Despite…
Personalized Imputation in metric spaces via conformal prediction: Applications in Predicting Diabetes Development with Continuous Glucose Monitoring Information
Marcos Matabuena, Carla Díaz-Louzao, Rahul Ghosal +1
The challenge of handling missing data is widespread in modern data analysis, particularly during the preprocessing phase and in various inferential modeling tasks. Although numero…
Screening for Diabetes Mellitus in the U.S. Population Using Neural Network Models and Complex Survey Designs
Marcos Matabuena, Juan C. Vidal, Rahul Ghosal +1
Complex survey designs are commonly employed in many medical cohorts. In such scenarios, developing case-specific predictive risk score models that reflect the unique characteristi…