School of Medicine

Center for Advanced Medical Analytics (CAMA)

Cell Maps for Artificial Intelligence

Cardiovascular Research Center

Department of Public Health Sciences

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31 to 36 of 36 Results

Replication Data for: Deep Learning-Derived Tissue Features Aid Diagnosis of Eosinophilic Esophagitis Jan 22, 2022 Adorno, William, 2021, "Replication Data for: Deep Learning-Derived Tissue Features Aid Diagnosis of Eosinophilic Esophagitis", https://doi.org/10.18130/V3/OJKSL9, University of Virginia Dataverse, V4 This contains data to replicate the eosionphil segmentation model and the EoE classification model.
Data Associated with the Publication: Vital Sign Metrics of VLBW Infants in Three NICUs: Implications for Predictive Algorithms Apr 7, 2021 - Center for Advanced Medical Analytics (CAMA) 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 Algorithms. Pediatric Research 2021. https://doi.org/10.1038/s41390-021-01428-3...
Evidence for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis Mar 31, 2021 Niestroy, Justin; Levinson, Maxwell; Al Manir, Sadnan; Clark, Timothy; Fairchild, Karen; Lake, Doug; Moorman, Randall, 2021, "Evidence for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis", https://doi.org/10.18130/V3/HHTAYI, University of Virginia Dataverse, V1 Evidence graph supporting "Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis".
Replication Data for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis Mar 26, 2021 - Center for Advanced Medical Analytics (CAMA) 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 - Center for Advanced Medical Analytics (CAMA) 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 Disease 2020. https://doi.org/10.1177/2048004020945142. ABSTRACT OBJEC...
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 - Center for Advanced Medical Analytics (CAMA) 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

Replication Data for: Deep Learning-Derived Tissue Features Aid Diagnosis of Eosinophilic Esophagitis

Jan 22, 2022

Adorno, William, 2021, "Replication Data for: Deep Learning-Derived Tissue Features Aid Diagnosis of Eosinophilic Esophagitis", https://doi.org/10.18130/V3/OJKSL9, University of Virginia Dataverse, V4

This contains data to replicate the eosionphil segmentation model and the EoE classification model.

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

Apr 7, 2021 - Center for Advanced Medical Analytics (CAMA)

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 Algorithms. Pediatric Research 2021. https://doi.org/10.1038/s41390-021-01428-3...

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

Mar 31, 2021

Niestroy, Justin; Levinson, Maxwell; Al Manir, Sadnan; Clark, Timothy; Fairchild, Karen; Lake, Doug; Moorman, Randall, 2021, "Evidence for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis", https://doi.org/10.18130/V3/HHTAYI, University of Virginia Dataverse, V1

Evidence graph supporting "Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis".

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

Mar 26, 2021 - Center for Advanced Medical Analytics (CAMA)

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 - Center for Advanced Medical Analytics (CAMA)

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 Disease 2020. https://doi.org/10.1177/2048004020945142. ABSTRACT OBJEC...

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 - Center for Advanced Medical Analytics (CAMA)

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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