Sylvain Baillet

@sylvain_baillet

Professor / Canada Research Chair: Neural Dynamics of Brain Systems / Assoc. Dean (Research) / Assoc. Editor

Montreal QC, Canada
Vrijeme pridruživanja: svibanj 2019.

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  1. Prikvačeni tweet
    3. pro 2019.

    Very proud of our paper just published in , a heroic effort by . 2 reasons: 1) I believe the approach sets a milestone for unpacking brain responses to naturalistic stimuli - here natural speech 2) it's my 100th peer-reviewed journal article. A thread.

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  2. Video abstract of our last paper with is now on channel : "Two Distinct Neural Timescales for Predictive Speech Processing"

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  4. 2. velj
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  5. proslijedio/la je Tweet
    31. sij

    coming out of . . Download it, use it, refine it. . Maybe you can build the next big breakthrough on this shared foundation.

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  6. proslijedio/la je Tweet
    31. sij

    Lab waste art installation. artist: Emily Brown – mjesto: McGill Life Sciences Complex

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  7. 31. sij

    Happy 25th birthday, FIL ! Thank you for 25 years of inspiration and continued neuroimaging excellence!

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  8. 31. sij

    Well done everyone ! For those who did not get one this round, perseverance and internal review first! 👨‍⚕️👩‍⚕️🤜🤛

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  9. 30. sij
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  10. 30. sij

    The app is to allow for clinicians to easily test out the models, provide feedback for improvement, generate interest in the possibilities of such tools + inspire others to replicate our approach. The code is available under a free open-source license!

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  11. 30. sij

    Jeremy took this all one step further designing a mobile web application () to allow non-programmers to explore and evaluate the predictive models. This is why Jeremy is such an amazing guy and scientist and future medical star doctor.

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  12. 30. sij

    We demonstrate that our models are capable of predicting meaningful individual-specific clinical outcome variables and show good generalizability across 16 SEER registries.

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  13. 30. sij

    We used balanced logistic regression-random forest ensemble classifiers and proportional hazards models to learn multivariate patterns of association between malignancy, survival, and a series of VERY basic clinical variables—such as tumor size, location, and surgical procedure.

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  14. 30. sij

    Jeremy developed methods and a practical app designed to assist with the diagnosis and prognosis of meningiomas. Statistical learning models were trained and validated on 62,844 patients from the Surveillance, Epidemiology, and End Results database.

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  15. 30. sij

    Thread / paper published today by our hero Jeremy Moreau, in co-supervision with neurosurgeon Roy Dudley. The power of harnessing simple but *BIG* data volumes to predict individual brain tumor outcomes.

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  17. 30. sij

    Out now in : fantastic work by Jeremy Moreau in the lab, in collab. with neurosurgeon extraordinaire Roy Dudley : from 60,000+ cases, to the prediction of outcome, and a mobile app. More on that soon.

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  18. 30. sij

    To fNIRS lovers out there. NIRSTORM is a free, open source plugin for .

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  19. 29. sij

    That's Martin Diers, not Dietz - sorry for the typo and thank you for your eagle eye!

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  20. 29. sij

    Open-access version via : Thanks to all collaborators involved, esp. Martin Dietz, Cecile de Vos & senior author Petra Schweinhardt ( & .)

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  21. 29. sij

    Our lab obsesses with the implementation of neural predictive mechanisms in perception & cognition, esp. via beta oscillatory signaling. We report today in that this pathway is also involved in the top-down modulation of pain perception.

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