Thomas Li
@_thomasli
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MD/PhD candidate @VanderbiltMSTP doing translational data science @MASI_Lab. #DukeU '18
Nashville, TN
Joined October 2016
Poster is up at #MICCAI2023! We discuss learning strategies for integrating longitudinal Imaging + EHRs. I will be at the 9:30 AM poster session (T-3-73) and then presenting at 4:30 PM (oral 7). Looking forward to my first MICCAI with @MASI_Lab!
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Someone throw the uworld 2ck qbank at this. Mine expiredβ¦
π¨ NEW Version of Glass AI Available π¨ Glass AI 2.0 combines an LLM with a clinical knowledge database created by our clinician team. With clinician training, we create better DDx and Clinical Plan outputs than base LLMs. Try 2.0 now at https://t.co/2FAkvJduXy
#medtwitter
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@LeonCai handed off the GitHub Guru trophy for lab mentorship. Thank you @_thomasli for filling his very big shoes. I appreciate our great @VanderbiltMSTP / @VandyBME team players.
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We are very interested in interpreting images within the context of a patient's history, known biomarkers, and other available data. However, all too often, not every patient has every data type available. Recently, we looked at this problem in lung screening.
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Our work on vision transformers for longitudinal medical imaging is out as preprint! We leverage time intervals b/w repeated scans to improve on a cross-sectional approach. https://t.co/2Ct6EGjHwt with @MASI_Lab @KXu63 @tangyc1183 @MaldonadoFabien @SandlerRhodes
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Great thread on understanding transformers from (roughly) first principles
Transformers are arguably the most impactful deep learning architecture from the last 5 yrs. In the next few threads, weβll cover multi-head attention, GPT and BERT, Vision Transformer, and write these out in code. This thread β understanding multi-head attention. 1/n
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The breadth that @EyeOn_AI covers is amazing - research, startups, policy, ethics, verticals... list goes on
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Brand new PredictionHealth video hot and fresh out of the oven! πΊπ©Ί π€ So psyched to be saving clinicians hours a day and freeing them up to focus on their patients. This is just the beginning, too!
You didn't go into medicine to spend hours in the EHR. Let AI-assisted scribes do your documentation for you. Introducing PredictionHealth.
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We would like to introduce Lucky (right) with her best friend (Leia) to the MSTPet community! Photo credit goes to Luckyβs human @_thomasli (M2).
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What company is the #1 market #EHR, makes >$3 billion/yr selling (aka gouging) health systems poor performing software, and now opposes @HHSGov proposal for hospitals to share medical data for their patients? This one: https://t.co/6vsNz4Z9TY by @chrissyfarr @CNBC
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A prospective clinical trial of #AI to determine intraoperative #cancer in near real time using label-free imaging: impressive rapid, accurate results by @umichneuro @ToddCHollon @DanOrringerMD & collaborators @NatureMedicine
https://t.co/nH6t20899U
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First Apple now Amazon. Interesting that they built out the mobile app and rx delivery but stopped short on hiring doctors. Instead they contracted with an existing provider
SCOOP: Amazon just launched Amazon Care, virtual medical clinics for its own employees. That includes pharmacy, virtual visits, and in-home care. https://t.co/vimgwK3tMe
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π€π’βΌοΈML Healthcare Researchers βΌοΈπ’π€ BIG medical data release thanks to @alistairewj @MIT @BIDMChealth MIMIC 2.0 >375k chest Xrays + ππππ ππππ ππΌπΏππππππ πππππππ Link: https://t.co/OjNsrQ65fp cc: @jeremyphoward @jeremy_irvin16
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Soooo excited to see this out @LancetDigitalH - deep learning for medical image classification by doctors @Moorfields with NO coding experience using @googlecloud #DeepLearning #AutoML #OpenSource
https://t.co/jV7Xy0hqXR
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Sad that I JUST discovered this paper. What's the equivalent technique for understanding representations from audio, text, ECG, genome... data?!!
Exploring Neural Networks with Activation Atlases -- A new Distill article by @shancarter, Zan Armstrong, @ludwigschubert, @enjalot, and @ch402. https://t.co/d8deVmNvfU
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