152 citations · 252 across the 5 of their papers we have counts for
5 papers
Added Value of Intraoperative Data for Predicting Postoperative Complications: Development and Validation of a MySurgeryRisk Extension
Shounak Datta, Tyler J. Loftus, Matthew M. Ruppert +12
To test the hypothesis that accuracy, discrimination, and precision in predicting postoperative complications improve when using both preoperative and intraoperative data input fea…
Improved Predictive Models for Acute Kidney Injury with IDEAs: Intraoperative Data Embedded Analytics
Lasith Adhikari, Tezcan Ozrazgat-Baslanti, Paul Thottakkara +5
Acute kidney injury (AKI) is a common and serious complication after a surgery which is associated with morbidity and mortality. The majority of existing perioperative AKI risk sco…
DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning
Benjamin Shickel, Tyler J. Loftus, Lasith Adhikari +3
Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static…
Nonconvex Regularization Based Sparse Recovery and Demixing with Application to Color Image Inpainting
Fei Wen, Lasith Adhikari, Ling Pei +3
This work addresses the recovery and demixing problem of signals that are sparse in some general dictionary. Involved applications include source separation, image inpainting, supe…
Trust-Region Methods for Sparse Relaxation
Lasith Adhikari, Jennifer B. Erway, Shelby Lockhart +1
In this paper, we solve the l2-l1 sparse recovery problem by transforming the objective function of this problem into an unconstrained differentiable function and apply a limited-m…