15 citations · 60 across the 12 of their papers we have counts for
6 papers · 1 filter
Real-time Mortality Prediction Using MIMIC-IV ICU Data Via Boosted Nonparametric Hazards
Zhale Nowroozilarki, Arash Pakbin, James Royalty +2
Electronic Health Record (EHR) systems provide critical, rich and valuable information at high frequency. One of the most exciting applications of EHR data is in developing a real-…
BoXHED2.0: Scalable boosting of dynamic survival analysis
Arash Pakbin, Xiaochen Wang, Bobak J. Mortazavi +1
Modern applications of survival analysis increasingly involve time-dependent covariates. The Python package BoXHED2.0 is a tree-boosted hazard estimator that is fully nonparametric…
Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural Networks
Lida Zhang, Nathan C. Hurley, Bassem Ibrahim +4
Blood pressure monitoring is an essential component of hypertension management and in the prediction of associated comorbidities. Blood pressure is a dynamic vital sign with freque…
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery
Zepeng Huo, Arash PakBin, Xiaohan Chen +6
Activity recognition in wearable computing faces two key challenges: i) activity characteristics may be context-dependent and change under different contexts or situations; ii) unk…
Explainable Prediction of Adverse Outcomes Using Clinical Notes
Justin R. Lovelace, Nathan C. Hurley, Adrian D. Haimovich +1
Clinical notes contain a large amount of clinically valuable information that is ignored in many clinical decision support systems due to the difficulty that comes with mining that…
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models
Randy Ardywibowo, Guang Zhao, Zhangyang Wang +3
Emerging wearable sensors have enabled the unprecedented ability to continuously monitor human activities for healthcare purposes. However, with so many ambient sensors collecting…