Aaron Lee
@aaronylee
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Retina Specialist, AI / ML / Deep Learning. C. Dan and Irene Hunter Endowed Professor of Ophthalmology. University of Washington
Joined February 2014
If you are attending MICCAI this year and are interested in ophthalmic imaging, please participate in the challenge being hosted by Mediwhale where our NIH Bridge2AI dataset (AI-READI) is being used!
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Thrilled to announce Cecilia & I will join @washumedicine where I'll serve as Chair of the John F. Hardesty, MD, Dept of Ophthalmology & Visual Sciences. Grateful to @UW & Russ Van Gelder for incredible mentorship, and Todd Margolis for his leadership!
medicine.washu.edu
Nationally recognized vitreoretinal surgeon leads efforts to apply AI to advance vision research, improve patient care
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Excited to announce the publication of our paper in Nature Communications showing a solution for arriving at the Retinal Pigment Score and finding biomarkers to use instead of race: ethnicity is not biology. Congrats to @anand_e_rajesh! https://t.co/CEBzeV9fyG
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V2 has more than a 1000 participants data and is available at
aireadi.org
Generating a flagship AI-ready and ethically-sourced dataset to support future AI-driven discoveries in diabetes
Here's an amazing multimodal dataset for #Ai research in type 2 #diabetes (clinical/EHR, imaging, labs, surveys, activity & glucose monitoring, environmental, etc. data...). Funded by @NIH_CommonFund, PIs @aaronylee and Cecilia Lee. @NatMetabolism paper:
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The inhome environmental sensor has some really interesting data and could give a lot more information about each individual’s exposome!
#ICYMI: from @UW, Cecilia Lee, @aaronylee & collaborators released the first data from a study of biomarkers and environmental factors that might influence the development of type 2 diabetes. @uwsomwwami #Bridge2AI
@NatMetabolism: https://t.co/D97AJHmEcj
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And read about our Marker Paper here!
nature.com
Nature Metabolism - Here, we introduce Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI), a multidisciplinary data-generation project designed to create and share a...
Read all about the latest #ArtificialIntelligence ready #data release by @aaronylee & team @UWMedicine! This dataset on Type 2 #diabetes will help researchers use #AI/#ML to discover new insights. https://t.co/zlhwpTYjE0
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#AIREADI Y2 data for #Bridge2AI is now live for download with >165,000 files, 2TB of data on #diabetes on >1000 people. Our marker paper was also published today at @NatMetabolism! https://t.co/rISKK2qobX Request access: https://t.co/Zd8HWSAjcE
#medtwitter #DataScience #AI
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Retinal vessel plexus differentiation based on OCTA using deep learning https://t.co/NN1xw8s6p0
@aaronylee
#ophthalmology
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If you use #datasets for #AI in #MedicalResearch, please help us understand whether Datasheets, Healthsheets, data card, data nutrition label, and accountability are best for #Transparency with this survey: https://t.co/r7rXyi5WW7
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Excited to share OCTCube ( https://t.co/fmcl0BhIuu), the first *3D* foundation model for retinal OCT images. OCTCube is trained on 26k 3D OCT volumes encompassing 1.62 million 2D images. OCTCube achieved significantly best performance on 27 out of 29 tasks.
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Thank you to everyone who came to #ARVO2024 in Seattle this year! It was an amazing conference and wonderful to see everyone again. So much brilliant work in the field for data science and AI in eyecare from around the world!
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.@NIH_CommonFund #Bridge2AI F2F @aaronylee presenting on AI-READI ( https://t.co/LgfpBL7rfC) - I’m proud of our collaborative work on new health data license- we consider downstream implications of AI - w/ Barbara Evans, Jorge Contreras, @SammHurstPhD @fairdataihub & Cecilia Lee
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April 18 and 19: @NIH_CommonFund Bridge2AI open house. Great opportunity for scientists, ethicists, coders, and clinicians, and others to learn about these flagship biomedical datasets & using them to answer big questions. Register: https://t.co/S0hAceGHrk
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Please come join us as we have our first open house for the NIH #Bridge2AI Program!!
If you're interested in #AI, want to learn about incredible multimodal biomedical datasets for analysis, and want to discuss key challenges (e.g., utility, ethics): Apply to attend the @NIH #Bridge2AI Open House (4/18-4/19, in-person or remote): https://t.co/H3M7l75quP
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Excited that our @DiabetesCareADA review paper and illustration on #AI was referenced by Forbes News! Congrats to @anand_e_rajesh
diabetesjournals.org
Current guidelines recommend that individuals with diabetes receive yearly eye exams for detection of referable diabetic retinopathy (DR), one of the leadi
Screening programs play a critical role in preventing complications of diabetic retinopathy, and the efficacy of these programs can be enhanced through artificial intelligence (AI).
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Lack of adoption of ocular imaging standards (DICOM) is bad for research & clinical care. @NatEyeInstitute @US_FDA @ONC_HealthIT have developed a roadmap for interoperability together. We will consider this strongly in future research grants @AAOjournal: https://t.co/wJ2sX376RX
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Bridge2AI F2F in the city of the stars ✨✨
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Everyone! If you know anyone who is interested in taking a supported year off to learn more about AI/ML, please ask them to apply to our internship program!
Applications are open for our NIH-funded mentored research internship program in #AI and #DataScience as part of the @NIH @Bridge2AI program! Applications open until Jan 15, 2024: https://t.co/hqLKfdjYY6
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Very interesting paper: using generative AI to produce text or images emits 3 to 4 orders of magnitude *less* CO2 than doing it manually or with the help of a computer. https://t.co/ErIPs4jCpM
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It was an honor to play a small part on this "foundational" work! #datascience #Ophthalmology #ophtwitter
1/ 🚨🚨 New paper alert 🚨🚨 Introducing RETFound, a foundation model for ophthalmology We’re super excited about this and hope it will act as a #Cornerstone for global efforts to prevent blindness through #AI
@UCLeye @Moorfields
#OpenAccess @Nature
https://t.co/DsvKgeUH5m
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