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LaussenLabs Profile
LaussenLabs

@LaussenLabs

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Multidisciplinary research lab focusing on systems physiology, data science, and machine learning in a pediatric critical care environment.

Toronto, Ontario
Joined September 2017
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@LaussenLabs
LaussenLabs
3 years
LaussenLabs is hosting Innovation Rounds. Would you like to attend?
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@PedCritCareMed
Pediatric Critical Care Medicine
4 years
FREE Feature article: Human Factors Analysis of Latent Safety Threats in a #PedsICU by Trbovich et al @laussen_peter 🇨🇦: https://t.co/TfcYojl0oI Editorial by @JessLaRosaMD et al @jimfackler: https://t.co/F09cjGjT4F @SCCM @WFPICCS
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@LaussenLabs
LaussenLabs
3 years
New publication out now!
@FrontDigiHealth
Frontiers in Digital Health
3 years
New research: An integration engineering framework for machine learning in healthcare https://t.co/8yHTCfn6LO #digitalhealth
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@SickKidsCCM
SickKids Critical Care Medicine
3 years
🚨Publication alert🚨 in @NatureMedicine! Congrats for this achievement to our very own Daniel Ehrmann, @sn_gallant, @sujnagaraj, Sebastian Goodfellow, @DannyEytan, Anna Goldenberg & Mjaye Mazwi from @LaussenLabs + @SickKidsNews ! >>🦾🧠 #AI and #MachineLearning in #PedsICU
@NatureMedicine
Nature Medicine
3 years
Evaluating and reducing cognitive load should be a priority for machine learning and artificial intelligence #AI in healthcare. Correspondence from Daniel E. Ehrmann and colleagues @sickkids https://t.co/q2NPu37JMw
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@LaussenLabs
LaussenLabs
4 years
We are thrilled to announce that our lab member and MASc candidate, Dmitrii Shubin recently presented a research poster at the Machine Learning in Healthcare (MLHC) conference, describing our time-efficient labelling framework. Read more: https://t.co/v9sOWQVjHP
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@ndrewg
Andrew Goodwin
6 years
"A practical approach to storage and retrieval of high-frequency physiological signals" https://t.co/0pDZtX8rbI Describes a database of physiological waveforms collected in a pediatric critical care unit. Over 720,000 patient-hours of data from more than 5300 patients. #pedsicu
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@rkamaleswaran
Rishi Kamaleswaran
6 years
“Human factors engineer needs to be in every critical care unit” @laussen_peter @LaussenLabs #CCC49 @sccm @SickKidsCCM
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@AzzyAssadi
Azzy A. NP, PhD
6 years
Inspired by human learning, circuits are now evolving to allow for faster and more efficient machine learning. @LaussenLabs
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@PICJournalWatch
PICU Journal Watch #PedsICU #PedsCICU
6 years
Impressive automated artefact detection methods from @LaussenLabs #jpccim2019 #PedsICU
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@laussen_peter
Peter Laussen
6 years
Game changing work presented by Andrew @LaussenLabs
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@LaussenLabs
LaussenLabs
7 years
Celebrating our 2 trillionth value collected by thanking the @SickKidsCCM staff that help us make it happen with this amazing cake! @laussen_peter
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@EmTee1982
Mark Todd
7 years
How Toronto's SickKids hopes to use AI to predict cardiac arrests
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@LaussenLabs
LaussenLabs
7 years
AtriumDB and LaussenLabs work featured as part of a first-of-its-kind announcement at Sick Kids @laussen_peter @SickKidsNews
theglobeandmail.com
Dr. Anna Goldenberg will be the hospital’s chair in biomedical informatics and artificial intelligence
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@VBrul
Val Brulé
7 years
One of the best talks I’ve ever heard on risk. “How do you deal with unknown unknowns? You stay humble.” @Gilwad @laussen_peter @LaussenLabs #RiskyBiz2018
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@SickKidsCCM
SickKids Critical Care Medicine
7 years
D Risky Business conference is here: Nov 5-6 @sheratonhotels @Toronto. Packed with amazing sessions on #AI, #ethics & #legal implications of #risk, #DecisionMaking & preparing for the #unexpected. Register now: https://t.co/xAXTVLjM4O @sickkids @laussen_peter #PedsICU @UofT @UHN
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@VBrul
Val Brulé
7 years
“The future is now!” Visionary leader in big data and healthcare technology. So lucky to always learn from him. Kind mentor to me and all critical care physicians. @CAPHCTweets @laussen_peter @LaussenLabs #CAPHC2018
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@sarah_gallie_rn
Sarah Gallie RN
7 years
Dr. Peter Laussen speaking about the future of healthcare with Artificial Intelligence #CAPHC2018 @SickKidsNews
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@LaussenLabs
LaussenLabs
7 years
LL Researcher Dr. Anusha Jegatheeswaran presenting her research on why high resolution physiological data is imperative when estimating a patient’s state. #MLHC2018
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@LaussenLabs
LaussenLabs
7 years
LL Researcher Sebastian Goodfellow presenting his work to lift the veil on ECG rhythm classification ML models at #mlhc2018
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@PICJournalWatch
PICU Journal Watch #PedsICU #PedsCICU
7 years
#MjayeMazwi impressive talk on #bigData @laussen_peter #WFPICCS18 #PedsICU key message for me: machine learning to identify latent variables to predict latent states; the white box, black box and grey box models; #bayesian
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