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Javid Dadashkarimi
@JDadashkarimi
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University of Pennsylvania, Yale '23, former developer at Martinos Center/MGH, medical image analysis š§ š·, deep learning, connectomics (he/him)
Philadelphia, PA
Joined June 2018
I love this quote from Benjamin Franklin: āEither write things worth reading, or do things worth writing.ā@pennbookstore
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RT @huili_sun: Very excited to share our work on infant brain age from @DScheinost's lab is out on @NatureComms! Heā¦
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@VardanArutiuni1 @ariConference congratulations! EEG is always fun especially when it blends with art : )
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RT @KavliAtYale: In a new @Yale study, @Yale_INP's Brendan Adkinson from the @DScheinost lab found that neuroimaging models š§ š» can be trainā¦
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RT @constable_todd: Submit your abstracts now (1 page to lesley.nadeau@yale.edu) for the Whistler Workshop, next Feb 23-26, 2025, and regisā¦
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RT @constable_todd: New work from @samardzija_anja and team. Instead of using CPM to identify networks, networks are predefined and used toā¦
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I had a wonderful time giving a talk at the Martinos Center's Super Group! A big thank you to Julie Price for the opportunity to share insights on #MachineLearning Tools in Computational #Neuroimaging: From #Connectomes to #FIT
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Honored to have coauthored and contributed to this amazing work! š āAssessing the generalizability of neuroimaging predictive models across diverse, unharmonized datasetsā
Can neuroimaging predictive models survive across diverse real-world data?š§ šWe put models to the test across 3 large-scale unharmonized datasets with over 2,800 participants. See our new work in this special issue of Developmental Cognitive Neuroscience:
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RT @constable_todd: Any trainees out there looking for a discussion on different career paths available? Come get advice from this panel atā¦
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RT @YaleNeuro: In a recent study, @YaleMed's Jean Ye, @ev_goldfarb, & @DScheinost used dynamic neuroimaging to uncover positiveā and negatiā¦
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