Su-In Lee

@suinleelab

Associate Professor in Paul G. Allen School of Computer Science & Engineering, University of Washington Computational biologist; bioinformatician; AI/ML expert

Seattle, WA
suinlee.cs.washington.edu
Vrijeme pridruživanja: kolovoz 2015.
3 fotografije ili videozapisa Fotografije i videozapisi

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  1. 27. sij

    Thank you, Stanford CCSB (Center for Cancer Systems Biology) for giving me such a great opportunity to give a seminar to such a brilliant group of people!

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  2. 27. sij

    I really appreciate my opportunity to give a talk at the PQG seminar (The Program in Quantitative Genomics )!

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  3. 27. sij

    I very much appreciate the opportunity to give a talk to such a brilliant group of people at MGH/Harvard. Thank you, Kamila!

    Please join us for a special seminar on explainable artificial intelligence in medicine by next Monday, December 2nd, 9:30 AM at MGH/Simches. Su-In is a great speaker - can't wait!
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  4. 24. sij

    Pascal's paper on the "expected gradient" is published:

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    17. sij

    "From local explanations to global understanding with explainable AI for trees" , by researchers , , Alex DeGrave, , Bala Nair, Ronit Katz, , , (4/4)

    Nature Machine Intelligence TreeExplainer cover image
    Korisnici , , i
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  6. 23. sij

    TreeExplainer is published as a cover article of the January issue of Nature Machine Intelligence. Congratulations, Scott, Gabe, Hugh, and Alex!

    A graphic showing a black box approach where an outcome ("Mortality value") is just spit out with no context and TreeExplainer, which shows how different health factors affect the outcome.
    “With TreeExplainer, we aim to break out of the so-called black box and understand how models arrive at their predictions," says prof about her lab's recent paper. Details:
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  7. 27. stu 2019.

    I did not expect my lab will receive this amazing award again. Gabe Erion and Joe Janizek are MD/CSE PhD students. Safiye Celik and Scott Lundberg were the winners in 2018 and 2017, respectively. I'm tremendously proud of you all!

    Three people smiling with arms around shoulders
    The CoAI team from & won the Madrona Prize recognizing excellence in research and commercial potential. CoAI is a machine learning method for predicting clinical outcomes to improve patient care. (2/6)
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  8. 12. stu 2019.

    It was a mind-blowing experience to give a talk at the MLD seminar at the Carnegie Mellon University and meet with eminent scientists in the field of machine learning. Thank you, Jian Ma and Barnabas Poczos for organizing my visit!

    Look forward to hosting Su-In Lee as ML/Duolingo seminar speaker at CMU on Tuesday Nov 12 |
    1 reply 1 proslijeđeni tweet 10 korisnika označava da im se sviđa
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  9. 5. stu 2019.

    Outstanding work by one of the best cancer biologists I know! Lymphatic metastases have more diverse roots than distant metastases

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  10. 19. lis 2019.

    New ideas are cheap; execution is hard - what my colleague said. Keep thinking how right it is.

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    11. lis 2019.

    Scanning through the submitted paper titles, and seeing a ton of very exciting work. I wish that I had time to read them all. Great job organizers on getting so much interest!

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    25. ruj 2019.

    Please visit our new MLCB website . MLCB registration is free and does not require paper submission. Due to space limit, we encourage to fill out the registration form.

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  13. 25. ruj 2019.

    Please visit our new MLCB website . MLCB registration is free and does not require paper submission. Due to space limit, we encourage to fill out the registration form.

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    5. ruj 2019.

    Machine Learning in Computational Biology (MLCB), Dec 13-14 2019, Vancouver -- The abstract deadline for MLCB is fast approaching (Oct 4th). Please submit your exciting research work to MLCB!

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  15. 8. ruj 2019.

    UW CSE is ranked #2...

    Very interesting statistics.
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  16. 5. ruj 2019.

    Machine Learning in Computational Biology (MLCB), Dec 13-14 2019, Vancouver -- The abstract deadline for MLCB is fast approaching (Oct 4th). Please submit your exciting research work to MLCB!

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  17. 9. kol 2019.

    Artificial intelligence scores another victory in diagnosing breast cancer via

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    9. kol 2019.

    ./@uwecenews and researchers have developed an system that could help pathologists read biopsies more accurately, and lead to better detection and diagnosis of . 🙌 |

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    4. kol 2019.

    Seattle Times on 's Anat Caspi​ and the Taskar Center for Accessible Technology. - With AI and other tech, Anat Caspi focuses on helping people with disabilities via

    5 proslijeđenih tweetova 13 korisnika označava da im se sviđa
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    11. velj 2018.

    Anat Caspi

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