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David P vanMaanen

Showing results (1-10 of 9) with videos related to

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Plos One|March 26, 2013
Development of antipsychotic medications with novel mechanisms of action based on computational modeling of hippocampal neuropathologyPeter J Siekmeier, David P vanMaanen
Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology|January 29, 2014
Dopaminergic contributions to hippocampal pathophysiology in schizophrenia: a computational studyPeter J Siekmeier, David P vanMaanen
IEEE Journal of Biomedical and Health Informatics|March 3, 2025
A Large-scale Multimodal Study for Predicting Mortality Risk Using Minimal and Low Parameter Models and Separable Risk AssessmentAlvaro Emilio Ulloa Cerna, David P vanMaanen, Linyuan Jing, et al.
The International Journal of Cardiovascular Imaging|February 24, 2022
Generalizability and quality control of deep learning-based 2D echocardiography segmentation models in a large clinical datasetXiaoyan Zhang, Alvaro E Ulloa Cerna, Joshua V Stough, et al.
Journal of Electrocardiology|November 27, 2022
An ECG-based machine learning model for predicting new-onset atrial fibrillation is superior to age and clinical features in identifying patients at high stroke riskSushravya Raghunath, John M Pfeifer, Christopher R Kelsey, et al.
Nature Genetics|February 18, 2022
Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK BiobankSean J Jurgens, Seung Hoan Choi, Valerie N Morrill, et al.
Nature Biomedical Engineering|February 9, 2021
Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortalityAlvaro E Ulloa Cerna, Linyuan Jing, Christopher W Good, et al.
Nature Medicine|May 13, 2020
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural networkSushravya Raghunath, Alvaro E Ulloa Cerna, Linyuan Jing, et al.
Circulation|February 16, 2021
Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation-Related StrokeSushravya Raghunath, John M Pfeifer, Alvaro E Ulloa-Cerna, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Plos One|March 26, 2013
Development of antipsychotic medications with novel mechanisms of action based on computational modeling of hippocampal neuropathologyPeter J Siekmeier, David P vanMaanen
Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology|January 29, 2014
Dopaminergic contributions to hippocampal pathophysiology in schizophrenia: a computational studyPeter J Siekmeier, David P vanMaanen
IEEE Journal of Biomedical and Health Informatics|March 3, 2025
A Large-scale Multimodal Study for Predicting Mortality Risk Using Minimal and Low Parameter Models and Separable Risk AssessmentAlvaro Emilio Ulloa Cerna, David P vanMaanen, Linyuan Jing, et al.
The International Journal of Cardiovascular Imaging|February 24, 2022
Generalizability and quality control of deep learning-based 2D echocardiography segmentation models in a large clinical datasetXiaoyan Zhang, Alvaro E Ulloa Cerna, Joshua V Stough, et al.
Journal of Electrocardiology|November 27, 2022
An ECG-based machine learning model for predicting new-onset atrial fibrillation is superior to age and clinical features in identifying patients at high stroke riskSushravya Raghunath, John M Pfeifer, Christopher R Kelsey, et al.
Nature Genetics|February 18, 2022
Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK BiobankSean J Jurgens, Seung Hoan Choi, Valerie N Morrill, et al.
Nature Biomedical Engineering|February 9, 2021
Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortalityAlvaro E Ulloa Cerna, Linyuan Jing, Christopher W Good, et al.
Nature Medicine|May 13, 2020
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural networkSushravya Raghunath, Alvaro E Ulloa Cerna, Linyuan Jing, et al.
Circulation|February 16, 2021
Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation-Related StrokeSushravya Raghunath, John M Pfeifer, Alvaro E Ulloa-Cerna, et al.
Pageof 1