Center for Advanced Medical Analytics (CAMA)

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1 to 7 of 7 Results

Pediatric Academic Societies 2024 NICU Mortality Prediction Challenge Mar 15, 2024 German Mesner, Ian, 2024, "Pediatric Academic Societies 2024 NICU Mortality Prediction Challenge", https://doi.org/10.18130/V3/5UYB4U, University of Virginia Dataverse, V6 Dataset for the Pediatric Academic Societies 2024 NICU Mortality Prediction Challenge
Replication Data for: Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants Feb 28, 2024 Lake, Douglas, 2024, "Replication Data for: Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants", https://doi.org/10.18130/V3/SASYHE, University of Virginia Dataverse, V2 Data associated with publication "Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants".
Data Associated with the Publication: Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms Apr 7, 2021 Zimmet, Amanda M; Sullivan, Brynne A; Fairchild, Karen D; Moorman, J Randall; Isler, Joseph R; Wallman-Stokes, Aaron W; Sahni, Rakesh; Vesoulis, Zachary A; Ratcliffe, Sarah J; Lake, Douglas E, 2021, "Data Associated with the Publication: Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms", https://doi.org/10.18130/V3/7UAPHU, University of Virginia Dataverse, V1 This repository contains the dataset and code for the manuscript: Zimmet AM, Sullivan BA, Fairchild KD, Moorman JR, Isler JR, Wallman-Stokes AW, Sahni R, Vesoulis ZA, Ratcliffe SJ, & Lake DE. Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithm...
Replication Data for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis Mar 26, 2021 Niestroy, Justin; Levinson, Maxwell; Al Manir, Sadnan; Clark, Timothy; Fairchild, Karen; Lake, Doug; Moorman, Randall, 2021, "Replication Data for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis", https://doi.org/10.18130/V3/VJXODP, University of Virginia Dataverse, V2, UNF:6:GqW9E/3oO1FhDufqdm3q5w== [fileUNF] Replication Data for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis
Trajectories of the heart rate characteristics index, a physiomarker of sepsis in premature infants, predict Neonatal ICU mortality Jul 30, 2020 Zimmet, Amanda M; Sullivan, Brynne A; Moorman, J Randall; Lake, Douglas E; Ratcliffe, Sarah J, 2020, "Trajectories of the heart rate characteristics index, a physiomarker of sepsis in premature infants, predict Neonatal ICU mortality", https://doi.org/10.18130/V3/2XENWC, University of Virginia Dataverse, V1, UNF:6:S3FYMHGFUcyal63xyeldrA== [fileUNF] This repository contains the dataset and code for the manuscript: Zimmet AM, Sullivan BA, Moorman JR, Lake DE, & Ratcliffe SJ. Trajectories of the heart rate characteristics index, a physiomarker of sepsis in premature infants, predict Neonatal ICU mortality. JRSM Cardiovascular...
UVA Holter Beat Annotation Files Jul 10, 2019 Lake, Douglas, 2019, "UVA Holter Beat Annotation Files", https://doi.org/10.18130/V3/TSJ8IC, University of Virginia Dataverse, V1, UNF:6:8CiN/EPHIGQW80jX0Qk0VQ== [fileUNF] Raw heart beat detection and annotation (.BEA) files for 2893 24-hour Holter recordings made at the University of Virginia from 2005 to 2010. Survival and basic patient information also available. Matlab script provided to read files and create interbeat intervals (i.e., RR inter...
Replication Data for: Cardiorespiratory dynamics measured from continuous ECG monitoring improves detection of deterioration in acute care patients: A retrospective cohort study Jul 17, 2017 Moss, Travis, 2017, "Replication Data for: Cardiorespiratory dynamics measured from continuous ECG monitoring improves detection of deterioration in acute care patients: A retrospective cohort study", https://doi.org/10.18130/V3/MKY17T, University of Virginia Dataverse, V1, UNF:6:X+2wSZbLeWoWG/3CELuVXw== [fileUNF] Minimal anonymized data set for replication of study findings

Pediatric Academic Societies 2024 NICU Mortality Prediction Challenge

Mar 15, 2024

German Mesner, Ian, 2024, "Pediatric Academic Societies 2024 NICU Mortality Prediction Challenge", https://doi.org/10.18130/V3/5UYB4U, University of Virginia Dataverse, V6

Dataset for the Pediatric Academic Societies 2024 NICU Mortality Prediction Challenge

Replication Data for: Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants

Feb 28, 2024

Lake, Douglas, 2024, "Replication Data for: Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants", https://doi.org/10.18130/V3/SASYHE, University of Virginia Dataverse, V2

Data associated with publication "Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants".

Data Associated with the Publication: Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms

Apr 7, 2021

Zimmet, Amanda M; Sullivan, Brynne A; Fairchild, Karen D; Moorman, J Randall; Isler, Joseph R; Wallman-Stokes, Aaron W; Sahni, Rakesh; Vesoulis, Zachary A; Ratcliffe, Sarah J; Lake, Douglas E, 2021, "Data Associated with the Publication: Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms", https://doi.org/10.18130/V3/7UAPHU, University of Virginia Dataverse, V1

This repository contains the dataset and code for the manuscript: Zimmet AM, Sullivan BA, Fairchild KD, Moorman JR, Isler JR, Wallman-Stokes AW, Sahni R, Vesoulis ZA, Ratcliffe SJ, & Lake DE. Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithm...

Replication Data for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis

Mar 26, 2021

Niestroy, Justin; Levinson, Maxwell; Al Manir, Sadnan; Clark, Timothy; Fairchild, Karen; Lake, Doug; Moorman, Randall, 2021, "Replication Data for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis", https://doi.org/10.18130/V3/VJXODP, University of Virginia Dataverse, V2, UNF:6:GqW9E/3oO1FhDufqdm3q5w== [fileUNF]

Replication Data for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis

Trajectories of the heart rate characteristics index, a physiomarker of sepsis in premature infants, predict Neonatal ICU mortality

Jul 30, 2020

Zimmet, Amanda M; Sullivan, Brynne A; Moorman, J Randall; Lake, Douglas E; Ratcliffe, Sarah J, 2020, "Trajectories of the heart rate characteristics index, a physiomarker of sepsis in premature infants, predict Neonatal ICU mortality", https://doi.org/10.18130/V3/2XENWC, University of Virginia Dataverse, V1, UNF:6:S3FYMHGFUcyal63xyeldrA== [fileUNF]

This repository contains the dataset and code for the manuscript: Zimmet AM, Sullivan BA, Moorman JR, Lake DE, & Ratcliffe SJ. Trajectories of the heart rate characteristics index, a physiomarker of sepsis in premature infants, predict Neonatal ICU mortality. JRSM Cardiovascular...

UVA Holter Beat Annotation Files

Jul 10, 2019

Lake, Douglas, 2019, "UVA Holter Beat Annotation Files", https://doi.org/10.18130/V3/TSJ8IC, University of Virginia Dataverse, V1, UNF:6:8CiN/EPHIGQW80jX0Qk0VQ== [fileUNF]

Raw heart beat detection and annotation (.BEA) files for 2893 24-hour Holter recordings made at the University of Virginia from 2005 to 2010. Survival and basic patient information also available. Matlab script provided to read files and create interbeat intervals (i.e., RR inter...

Replication Data for: Cardiorespiratory dynamics measured from continuous ECG monitoring improves detection of deterioration in acute care patients: A retrospective cohort study

Jul 17, 2017

Moss, Travis, 2017, "Replication Data for: Cardiorespiratory dynamics measured from continuous ECG monitoring improves detection of deterioration in acute care patients: A retrospective cohort study", https://doi.org/10.18130/V3/MKY17T, University of Virginia Dataverse, V1, UNF:6:X+2wSZbLeWoWG/3CELuVXw== [fileUNF]

Minimal anonymized data set for replication of study findings

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