activity
20182020
most citedDevelopment and validation of computable Phenotype to Identify and Characterize Kidney Health in Adult Hospitalized Patients

8 citations · 9 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2020

Application of Deep Interpolation Network for Clustering of Physiologic Time Series

Yanjun Li, Yuanfang Ren, Tyler J. Loftus +7

Background: During the early stages of hospital admission, clinicians must use limited information to make diagnostic and treatment decisions as patient acuity evolves. However, it…

cs.CY20191 cited

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…

cs.HC2019

The DREAMS Project: Improving the Intensive Care Patient Experience with Virtual Reality

Triton Ong, Matthew Ruppert, Parisa Rashidi +3

Purpose: Preliminarily evaluate the feasibility and efficacy of using meditative virtual reality (VR) to improve the hospital experience of intensive care unit (ICU) patients. Meth…

stat.AP20198 cited

Development and validation of computable Phenotype to Identify and Characterize Kidney Health in Adult Hospitalized Patients

Tezcan Ozrazgat-Baslanti, Amir Motaei, Rubab Islam +7

Background: Acute kidney injury (AKI) is a common complication in hospitalized patients and a common cause for chronic kidney disease (CKD) and increased hospital cost and mortalit…

cs.HC2018

The Intelligent ICU Pilot Study: Using Artificial Intelligence Technology for Autonomous Patient Monitoring

Anis Davoudi, Kumar Rohit Malhotra, Benjamin Shickel +8

Currently, many critical care indices are repetitively assessed and recorded by overburdened nurses, e.g. physical function or facial pain expressions of nonverbal patients. In add…