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AnimaAnandkumar's profile
Prof. Anima Anandkumar
Prof. Anima Anandkumar
Prof. Anima Anandkumar
@AnimaAnandkumar

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Prof. Anima Anandkumar

@AnimaAnandkumar

Director of #AI #research @nvidia, Bren #Professor @Caltech, Fmr Principal scientist @awscloud #Sloan fellow #Tensors Erdos #2 #dancer http://anima-ai.org 

Santa Clara, CA
tensorlab.cms.caltech.edu/users/anima/
Joined October 2014

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    Prof. Anima Anandkumar‏ @AnimaAnandkumar 14 Oct 2019
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    Prof. Anima Anandkumar Retweeted Ben Recht

    #AI for #healthcare and in particular #medicalimaging has a lot of potential. There should be big investments in #research and data collection. #AInotready Let us not apply the #siliconvalley ethos of "move fast break things" @EricTopolhttps://twitter.com/beenwrekt/status/1183745028696395776 …

    Prof. Anima Anandkumar added,

    Ben Recht @beenwrekt
    Seems troubling: Many of the images in the CXR-14 chest x-ray data set are post treatment and have chest drains in the images. Once these examples are removed, machine learning performs worse than a first year resident. h/t @DrLukeOR https://arxiv.org/abs/1909.12475 
    11:39 AM - 14 Oct 2019
    • 15 Retweets
    • 62 Likes
    • Rutuja Jadhav Sukriti Paul ContextAI HotComputerScience Daniel Coelho de Castro Andrew Murphy marcel blattner Turki Alelyani🤗🧠 Anoop Kulkarni, PhD
    5 replies 15 retweets 62 likes
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      2. Harish Prabhala‏ @prabhalah 14 Oct 2019
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        Replying to @AnimaAnandkumar @EricTopol

        Agreed. But where will the big investments come from for this data collection? Govt grants or VCs? Grants take time and have intense competition. VCs have no patience in investing in companies with high gestation periods. How do we collect quality data in med imaging?

        1 reply 0 retweets 1 like
      3. Prof. Anima Anandkumar‏ @AnimaAnandkumar 14 Oct 2019
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        Replying to @prabhalah @EricTopol

        I hope the VCs change their strategy and focus on impact investing. Instead of throwing money on oversaturated ideas I hope they get more creative. I hope philanthropy also recognizes the value and not dismiss this as mundane data collection

        2 replies 0 retweets 2 likes
      4. Show replies
      1. Supriyo SB Chatterjee‏ @sbc111 14 Oct 2019
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        Replying to @AnimaAnandkumar @EricTopol

        In the case of #AI #healthcare applications - it's more complex. Data management is critical to ensure the quality of data. A recent post from @nresearchnews - The “inconvenient truth” about AI in healthcare -https://www.nature.com/articles/s41746-019-0155-4 …

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      1. (((Anthony Samir)))‏ @anthonysamir 14 Oct 2019
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        Replying to @AnimaAnandkumar @EricTopol

        I have an ML R01 from NIH and similar funding from DoD and industry. This is not a private industry play: timelines are too long and revenue too uncertain. Unfortunately, there is no - zero - coherent government strategy for medical imaging AI tool development.

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      1. Syed Abid Hussain‏ @SplineAI 15 Oct 2019
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        Replying to @AnimaAnandkumar @EricTopol

        I always doubt the CXR-14 data. I think someone re-validate the CXR-14 data removing the doubtful labels. Analytics with CXR-14 may be at best a second opinion to radiologists rather than a correct diagnosis

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      1. Anoop Kulkarni, PhD‏ @DrAnoopKulkarni 15 Oct 2019
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        Replying to @AnimaAnandkumar @EricTopol

        Ironical as it may sound, these days i spend more time telling folks to slow down in healthcare AI. Sadly, in India, we yet haven't moved fast enough to have a regulatory framework in place. In the meantime, hospitals / clinics talk of deploying software, which is bit worrisome

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