David Sontag

@david_sontag

Associate Professor at MIT and Chief Health Strategist at ASAPP

Massachusetts Institute of Technology
Vrijeme pridruživanja: veljača 2012.

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  1. Prikvačeni tweet
    10. lis 2019.

    It *is* possible to get high-quality structured data from electronic medical records AND to save time; one just needs to re-think the user interface (and use machine learning). Here's a taste of the future: (w/ Steven Horng )

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  2. proslijedio/la je Tweet
    3. velj

    Alright. Inspired by this tweet, I decided to read all relevant preprints (about 30 in all). Here's what I've found, a thread. 1/15

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  3. 26. sij
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  4. proslijedio/la je Tweet
    25. sij

    A new dedicated issue on in (via ) My bit on the big potential impact: Care is the human bond, and we’ve largely lost that. We’ve got to get it back.

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  5. 24. sij
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  6. 24. sij

    I started my talk this morning at the AI Latin American Summit showing a Spanish-language book on artificial intelligence written by my father, Eduardo Sontag. What year do you think he wrote it?

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  7. proslijedio/la je Tweet
    23. sij

    Para mejorar la salud a través de , de presenta su visión de augmenting patients y la necesidad de una historia clínica potenciada por AI para mejorar el contexto del historial y la captura de dolencias en el diagnóstico.

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  8. proslijedio/la je Tweet
    23. sij

    Why AI for healthcare is a hard but interesting challenge both from the algortihmic point of view and for the health system. Amazing talk by with a touching introduction (he gave in Spanish!)

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  9. 14. sij

    New MIT-Takeda partnership will fund 6-10 joint research projects per year and 11 graduate fellowships in AI & healthcare. Each project will bring together 2+ MIT faculty and Takeda researchers from around the world.

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  10. 14. sij

    "How many workflows will be affected? Does the model increase the efficiency of existing workflows? Is the model being deployed within an existing digital workflow?"

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  11. 13. sij

    It was great to visit the ASAPP Argentina office for the first time!

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  12. proslijedio/la je Tweet
    8. sij

    Introducing the latest episode of Theory and Practice: , Associate Professor of Electrical Engineering and Computer Science at , explores how artificial intelligence can transform medicine –

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  13. proslijedio/la je Tweet
    14. pro 2019.

    The fantastic women keynote speakers Ying-Qi Zhao & Andrea Rotnitzky at the workshop on causal inference on a panel moderated by

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  14. 13. pro 2019.

    "Studies found that when CAD failed to correctly prompt a cancer, subjects with CAD assistance performed significantly worse than unassisted readers", at his talk. , what's the reference?

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  15. proslijedio/la je Tweet
    13. pro 2019.

    If you'd like to read the best of the 340 papers submitted to this year, they have been posted on the website: A big THANK YOU to all of the reviewers who helped turned these around in 2 weeks!

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  16. proslijedio/la je Tweet
    11. pro 2019.

    I'm excited to announce that Tech Fellow will become director of our three Northeast Labs: MSR New England, MSR NYC & MSR Montreal. You can listen to Susan's at

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  17. 11. pro 2019.

    , I'm on my way! Sorry for the delay; was in Boston last night.

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  18. 8. pro 2019.

    Jonas Peters and I are the program chairs for . Paper deadline is Feb 20, 2020, and conference will be in Toronto, Aug 3-6, 2020. General chairs are and . Consider submitting your best work!

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  19. proslijedio/la je Tweet
    3. pro 2019.

    Check out our paper (collaboration with , , etc. at Research's Science for Social Good Initiative) on synthesizing evidence, which will be presented at the ML4H Workshop and IAAI conference : .

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  20. 3. pro 2019.

    Wow! CHiQA: an experimental AI system for answering health-related questions for patients See paper & new (publicly available) datasets just published in JAMIA '19 by Demner-Fushman and colleagues

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  21. proslijedio/la je Tweet
    23. stu 2019.
    Odgovor korisnicima i sljedećem broju korisnika:

    In our new paper with and Shie Mannor we go into quite a bit of detail defining OPE in partially observable RL scenarios, and tying it back to causal defitinions

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