Search Results for author: Ziyuan Guan

Found 11 papers, 0 papers with code

A multi-cohort study on prediction of acute brain dysfunction states using selective state space models

no code implementations11 Mar 2024 Brandon Silva, Miguel Contreras, Sabyasachi Bandyopadhyay, Yuanfang Ren, Ziyuan Guan, Jeremy Balch, Kia Khezeli, Tezcan Ozrazgat Baslanti, Ben Shickel, Azra Bihorac, Parisa Rashidi

Our research fills these gaps in the existing literature by dynamically predicting delirium, coma, and mortality for 12-hour intervals throughout an ICU stay and validating on two public datasets.

Temporal Cross-Attention for Dynamic Embedding and Tokenization of Multimodal Electronic Health Records

no code implementations6 Mar 2024 Yingbo Ma, Suraj Kolla, Dhruv Kaliraman, Victoria Nolan, Zhenhong Hu, Ziyuan Guan, Yuanfang Ren, Brooke Armfield, Tezcan Ozrazgat-Baslanti, Tyler J. Loftus, Parisa Rashidi, Azra Bihorac, Benjamin Shickel

The breadth, scale, and temporal granularity of modern electronic health records (EHR) systems offers great potential for estimating personalized and contextual patient health trajectories using sequential deep learning.

Time Series

Detecting Visual Cues in the Intensive Care Unit and Association with Patient Clinical Status

no code implementations1 Nov 2023 Subhash Nerella, Ziyuan Guan, Andrea Davidson, Yuanfang Ren, Tezcan Baslanti, Brooke Armfield, Patrick Tighe, Azra Bihorac, Parisa Rashidi

We leveraged our AU-ICU dataset with 107, 064 frames collected in the ICU annotated with facial action units (AUs) labels by trained annotators.

Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures

no code implementations27 Jul 2023 Yuanfang Ren, Yanjun Li, Tyler J. Loftus, Jeremy Balch, Kenneth L. Abbott, Shounak Datta, Matthew M. Ruppert, Ziyuan Guan, Benjamin Shickel, Parisa Rashidi, Tezcan Ozrazgat-Baslanti, Azra Bihorac

With clustering analysis for vital signs within six hours of admission, patient phenotypes with distinct pathophysiological signatures and outcomes may support early clinical decisions.

Clustering

AI-Enhanced Intensive Care Unit: Revolutionizing Patient Care with Pervasive Sensing

no code implementations11 Mar 2023 Subhash Nerella, Ziyuan Guan, Scott Siegel, Jiaqing Zhang, Kia Khezeli, Azra Bihorac, Parisa Rashidi

However, the extent of patient monitoring in the ICU is limited due to time constraints and the workload on healthcare providers.

Computable Phenotypes to Characterize Changing Patient Brain Dysfunction in the Intensive Care Unit

no code implementations9 Mar 2023 Yuanfang Ren, Tyler J. Loftus, Ziyuan Guan, Rayon Uddin, Benjamin Shickel, Carolina B. Maciel, Katharina Busl, Parisa Rashidi, Azra Bihorac, Tezcan Ozrazgat-Baslanti

We developed algorithms to quantify acute brain dysfunction status including coma, delirium, normal, or death at 12-hour intervals of each ICU admission and to identify acute brain dysfunction phenotypes using continuous acute brain dysfunction status and k-means clustering approach.

Decision Making ICU Mortality

Clinical Courses of Acute Kidney Injury in Hospitalized Patients: A Multistate Analysis

no code implementations8 Mar 2023 Esra Adiyeke, Yuanfang Ren, Ziyuan Guan, Matthew M. Ruppert, Parisa Rashidi, Azra Bihorac, Tezcan Ozrazgat-Baslanti

At 14 days following Stage 1 AKI, patients with more frail conditions (Charlson comorbidity index greater than or equal to 3 and had prolonged ICU stay) had lower proportion of transitioning to No AKI or discharge states.

Application of Deep Interpolation Network for Clustering of Physiologic Time Series

no code implementations27 Apr 2020 Yanjun Li, Yuanfang Ren, Tyler J. Loftus, Shounak Datta, M. Ruppert, Ziyuan Guan, Dapeng Wu, Parisa Rashidi, Tezcan Ozrazgat-Baslanti, Azra Bihorac

M Interpretation: In a heterogeneous cohort of hospitalized patients, a deep interpolation network extracted representations from vital sign data measured within six hours of hospital admission.

Clustering Time Series +1

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