15 citations · 60 across the 12 of their papers we have counts for
12 papers
Predicting the meal macronutrient composition from continuous glucose monitors
Zepeng Huo, Bobak J. Mortazavi, Theodora Chaspari +3
Sustained high levels of blood glucose in type 2 diabetes (T2DM) can have disastrous long-term health consequences. An essential component of clinical interventions for T2DM is mon…
Boosted-SpringDTW for Comprehensive Feature Extraction of Physiological Signals
Jonathan Martinez, Kaan Sel, Bobak J. Mortazavi +1
Goal: To achieve-high quality comprehensive feature extraction from physiological signals that enables precise physiological parameter estimation despite evolving waveform morpholo…
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…
Dynamically Extracting Outcome-Specific Problem Lists from Clinical Notes with Guided Multi-Headed Attention
Justin Lovelace, Nathan C. Hurley, Adrian D. Haimovich +1
Problem lists are intended to provide clinicians with a relevant summary of patient medical issues and are embedded in many electronic health record systems. Despite their importan…
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…
BoXHED: Boosted eXact Hazard Estimator with Dynamic covariates
Xiaochen Wang, Arash Pakbin, Bobak J. Mortazavi +2
The proliferation of medical monitoring devices makes it possible to track health vitals at high frequency, enabling the development of dynamic health risk scores that change with…
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…
A Survey of Challenges and Opportunities in Sensing and Analytics for Cardiovascular Disorders
Nathan C. Hurley, Erica S. Spatz, Harlan M. Krumholz +2
Cardiovascular disorders account for nearly 1 in 3 deaths in the United States. Care for these disorders are often determined during visits to acute care facilities, such as hospit…
Visualization of Emergency Department Clinical Data for Interpretable Patient Phenotyping
Nathan C. Hurley, Adrian D. Haimovich, R. Andrew Taylor +1
Visual summarization of clinical data collected on patients contained within the electronic health record (EHR) may enable precise and rapid triage at the time of patient presentat…
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…