Výsledky vyhledávání - "Subbian, Vignesh"

Akademický článek

Identifying Barriers to and Opportunities for Telehealth Implementation Amidst the COVID-19 Pandemic by Using a Human Factors Approach: A Leap Into the Future of Health Care Delivery?

Autor: Zhang, Tianyi, Mosier, Jarrod, Subbian, Vignesh

Publikováno v: JMIR Human Factors, Vol 8, Iss 2, p e24860 (2021)

The extensive uptake of telehealth has considerably transformed health care delivery since the beginning of the COVID-19 pandemic and has imposed tremendous challenges to its large-scale implementation and adaptation. Given the shift in paradigm from

Externí odkaz: https://doaj.org/article/4fe2b14616774eaba22c544b0c3cd3f3

Zobrazit plný text záznamu

Akademický článek

Decompensation in Critical Care: Early Prediction of Acute Heart Failure Onset

Autor: Essay, Patrick, Balkan, Baran, Subbian, Vignesh

Publikováno v: JMIR Medical Informatics, Vol 8, Iss 8, p e19892 (2020)

BackgroundHeart failure is a leading cause of mortality and morbidity worldwide. Acute heart failure, broadly defined as rapid onset of new or worsening signs and symptoms of heart failure, often requires hospitalization and admission to the intensiv

Externí odkaz: https://doaj.org/article/3de2716d9dfd4959bb9afb3bc4d1d5d9

Zobrazit plný text záznamu

Akademický článek

Rule-Based Cohort Definitions for Acute Respiratory Failure: Electronic Phenotyping Algorithm

Autor: Essay, Patrick, Mosier, Jarrod, Subbian, Vignesh

Publikováno v: JMIR Medical Informatics, Vol 8, Iss 4, p e18402 (2020)

BackgroundAcute respiratory failure is generally treated with invasive mechanical ventilation or noninvasive respiratory support strategies. The efficacies of the various strategies are not fully understood. There is a need for accurate therapy-based

Externí odkaz: https://doaj.org/article/9708e6d8e3c7439daa2073b142d7bccb

Zobrazit plný text záznamu

Report

Discovery of Generalizable TBI Phenotypes Using Multivariate Time-Series Clustering

Autor: Ghaderi, Hamid, Foreman, Brandon, Reddy, Chandan K., Subbian, Vignesh

Publikováno v: Computers in Biology and Medicine, Volume 180, September 2024, 108997

Traumatic Brain Injury (TBI) presents a broad spectrum of clinical presentations and outcomes due to its inherent heterogeneity, leading to diverse recovery trajectories and varied therapeutic responses. While many studies have delved into TBI phenot

Externí odkaz: http://arxiv.org/abs/2401.08002

Zobrazit plný text záznamu

Akademický článek

The bidirectional gut-brain-microbiota axis as a potential nexus between traumatic brain injury, inflammation, and disease

Autor: Sundman, Mark H., Chen, Nan-kuei, Subbian, Vignesh, Chou, Ying-hui

As head injuries and their sequelae have become an increasingly salient matter of public health, experts in the field have made great progress elucidating the biological processes occurring within the brain at the moment of injury and throughout the

Externí odkaz: http://hdl.handle.net/10150/626124
http://arizona.openrepository.com/arizona/handle/10150/626124

Zobrazit plný text záznamu

Akademický článek

Tissue Augmentation with Allograft Adipose Matrix For the Diabetic Foot in Remission

Autor: Shahin, Tala B., Vaishnav, Kairavi V., Watchman, Marcy, Subbian, Vignesh, Larson, Ethan, Chnari, Evangelia, Armstrong, David G.

Background: Repetitive stress on the neuropathic plantar foot is the primary cause of diabetic foot ulcers. After healing, recurrence is common. Modulating plantar pressure has been associated with extension of ulcer free days. Therefore, the goal of

Externí odkaz: http://hdl.handle.net/10150/626285
http://arizona.openrepository.com/arizona/handle/10150/626285

Zobrazit plný text záznamu

Report

Identifying TBI Physiological States by Clustering Multivariate Clinical Time-Series Data

Autor: Ghaderi, Hamid, Foreman, Brandon, Nayebi, Amin, Tipirneni, Sindhu, Reddy, Chandan K., Subbian, Vignesh

Publikováno v: AMIA Annu Symp Proc. 2024 Jan 11;2023:379-388

Determining clinically relevant physiological states from multivariate time series data with missing values is essential for providing appropriate treatment for acute conditions such as Traumatic Brain Injury (TBI), respiratory failure, and heart fai

Externí odkaz: http://arxiv.org/abs/2303.13024

Zobrazit plný text záznamu

Report

Computable Phenotypes for Post-acute sequelae of SARS-CoV-2: A National COVID Cohort Collaborative Analysis

Autor: Pungitore, Sarah, Olorunnisola, Toluwanimi, Mosier, Jarrod, Subbian, Vignesh

Post-acute sequelae of SARS-CoV-2 (PASC) is an increasingly recognized yet incompletely understood public health concern. Several studies have examined various ways to phenotype PASC to better characterize this heterogeneous condition. However, many

Externí odkaz: http://arxiv.org/abs/2303.12813

Zobrazit plný text záznamu

Report

A Self-Supervised Learning-based Approach to Clustering Multivariate Time-Series Data with Missing Values (SLAC-Time): An Application to TBI Phenotyping

Autor: Ghaderi, Hamid, Foreman, Brandon, Nayebi, Amin, Tipirneni, Sindhu, Reddy, Chandan K., Subbian, Vignesh

Self-supervised learning approaches provide a promising direction for clustering multivariate time-series data. However, real-world time-series data often include missing values, and the existing approaches require imputing missing values before clus

Externí odkaz: http://arxiv.org/abs/2302.13457

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání