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Video-based AI for beat-to-beat assessment of cardiac function 期刊论文
NATURE, 2020, 580 (7802) : 252-+
作者:  Pleguezuelos-Manzano, Cayetano;  Puschhof, Jens;  Huber, Axel Rosendahl;  van Hoeck, Arne;  Wood, Henry M.;  Nomburg, Jason;  Gurjao, Carino;  Manders, Freek;  Dalmasso, Guillaume;  Stege, Paul B.;  Paganelli, Fernanda L.;  Geurts, Maarten H.;  Beumer, Joep;  Mizutani, Tomohiro;  Miao, Yi;  van der Linden, Reinier;  van der Elst, Stefan;  Garcia, K. Christopher;  Top, Janetta;  Willems, Rob J. L.;  Giannakis, Marios;  Bonnet, Richard;  Quirke, Phil;  Meyerson, Matthew;  Cuppen, Edwin;  van Boxtel, Ruben;  Clevers, Hans
收藏  |  浏览/下载:117/0  |  提交时间:2020/07/03

A video-based deep learning algorithm-EchoNet-Dynamic-accurately identifies subtle changes in ejection fraction and classifies heart failure with reduced ejection fraction using information from multiple cardiac cycles.


Accurate assessment of cardiac function is crucial for the diagnosis of cardiovascular disease(1), screening for cardiotoxicity(2) and decisions regarding the clinical management of patients with a critical illness(3). However, human assessment of cardiac function focuses on a limited sampling of cardiac cycles and has considerable inter-observer variability despite years of training(4,5). Here, to overcome this challenge, we present a video-based deep learning algorithm-EchoNet-Dynamic-that surpasses the performance of human experts in the critical tasks of segmenting the left ventricle, estimating ejection fraction and assessing cardiomyopathy. Trained on echocardiogram videos, our model accurately segments the left ventricle with a Dice similarity coefficient of 0.92, predicts ejection fraction with a mean absolute error of 4.1% and reliably classifies heart failure with reduced ejection fraction (area under the curve of 0.97). In an external dataset from another healthcare system, EchoNet-Dynamic predicts the ejection fraction with a mean absolute error of 6.0% and classifies heart failure with reduced ejection fraction with an area under the curve of 0.96. Prospective evaluation with repeated human measurements confirms that the model has variance that is comparable to or less than that of human experts. By leveraging information across multiple cardiac cycles, our model can rapidly identify subtle changes in ejection fraction, is more reproducible than human evaluation and lays the foundation for precise diagnosis of cardiovascular disease in real time. As a resource to promote further innovation, we also make publicly available a large dataset of 10,030 annotated echocardiogram videos.


  
Cumulative biomass curves describe past and present conditions of Large Marine Ecosystems 期刊论文
GLOBAL CHANGE BIOLOGY, 2019
作者:  Pranovi, Fabio;  Libralato, Simone;  Zucchetta, Matteo;  Monti, Marco Anelli;  Link, Jason S.
收藏  |  浏览/下载:5/0  |  提交时间:2019/11/27
cumulative biomass  Ecosystem Approach  ecosystem indicators  emergent properties  trophic level  
Large-scale distribution of tuna species in a warming ocean 期刊论文
GLOBAL CHANGE BIOLOGY, 2019, 25 (6) : 2043-2060
作者:  Erauskin-Extramiana, Maite;  Arrizabalaga, Haritz;  Hobday, Alistair J.;  Cabre, Anna;  Ibaibarriaga, Leire;  Arregui, Igor;  Murua, Hilario;  Chust, Guillem
收藏  |  浏览/下载:14/0  |  提交时间:2019/11/26
climate change  exclusive economic zone  future projections  poleward shift  species distribution model  tuna  
Conventional land-use intensification reduces species richness and increases production: A global meta-analysis 期刊论文
GLOBAL CHANGE BIOLOGY, 2019, 25 (6) : 1941-1956
作者:  Beckmann, Michael;  Gerstner, Katharina;  Akin-Fajiye, Morodoluwa;  Ceausu, Silvia;  Kambach, Stephan;  Kinlock, Nicole L.;  Phillips, Helen R. P.;  Verhagen, Willem;  Gurevitch, Jessica;  Klotz, Stefan;  Newbold, Tim;  Verburg, Peter H.;  Winter, Marten;  Seppelt, Ralf
收藏  |  浏览/下载:11/0  |  提交时间:2019/11/26
arable fields  biodiversity  conservation  crop production  forests  grasslands  green fodder  land management  wood production  
Global assessment of marine biodiversity potentially threatened by offshore hydrocarbon activities 期刊论文
GLOBAL CHANGE BIOLOGY, 2019, 25 (6) : 2009-2020
作者:  Venegas-Li, Ruben;  Levin, Noam;  Morales-Barquero, Lucia;  Kaschner, Kristin;  Garilao, Cristina;  Kark, Salit
收藏  |  浏览/下载:9/0  |  提交时间:2019/11/26
energy  marine biodiversity  ocean  offshore hydrocarbon  oil and gas  species richness  
Four decades of functional community change reveals gradual trends and low interlinkage across trophic groups in a large marine ecosystem 期刊论文
GLOBAL CHANGE BIOLOGY, 2019, 25 (4) : 1235-1246
作者:  Tornroos, Anna;  Pecuchet, Laurene;  Olsson, Jens;  Gardmark, Anna;  Blomqvist, Mats;  Lindegren, Martin;  Bonsdorff, Erik
收藏  |  浏览/下载:11/0  |  提交时间:2019/04/09
Baltic Sea  coastal ecosystem  community dynamics  fish  functional diversity  functional turnover  multifunctionality  temporal change  trait-based approach  zoobenthos  
Susceptibility of European freshwater fish to climate change: Species profiling based on life-history and environmental characteristics 期刊论文
GLOBAL CHANGE BIOLOGY, 2019, 25 (2) : 448-458
作者:  Jaric, Ivan;  Lennox, Robert J.;  Kalinkat, Gregor;  Cvijanovic, Gorcin;  Radinger, Johannes
收藏  |  浏览/下载:9/0  |  提交时间:2019/04/09
climate change  extinction threat  global warming  IUCN  Red List  
Dynamic response and hydrodynamics of polarized crowds 期刊论文
SCIENCE, 2019, 363 (6422) : 46-+
作者:  Bain, Nicolas;  Bartolo, Denis
收藏  |  浏览/下载:0/0  |  提交时间:2019/11/27
Multimodel ensembles improve predictions of crop-environment-management interactions 期刊论文
GLOBAL CHANGE BIOLOGY, 2018, 24 (11) : 5072-5083
作者:  Wallach, Daniel;  39;Leary, Garry J.
收藏  |  浏览/下载:7/0  |  提交时间:2019/04/09
climate change impact  crop models  ensemble mean  ensemble median  multimodel ensemble  prediction  
Modelled biophysical impacts of conservation agriculture on local climates 期刊论文
GLOBAL CHANGE BIOLOGY, 2018, 24 (10) : 4758-4774
作者:  Hirsch, Annette L.;  Prestele, Reinhard;  Davin, Edouard L.;  Seneviratne, Sonia I.;  Thiery, Wim;  Verburg, Peter H.
收藏  |  浏览/下载:10/0  |  提交时间:2019/04/09
CESM  climate-effective land management  CLM  land-based mitigation  subgrid-scale influences  temperature extremes  tillage