DREAMchallenges
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DREAMchallenges
@DR_E_A_M
DREAM is the Dialogue for Reverse Engineering Assessments and methods. @dreamchallenges.bsky.social

Here is the hard truth: The AI medical device boom is outpacing the people who regulate it. This study shows LLMs can reliably extract key details from dense FDA-style regulatory documents (often ~80%+ accuracy), enabling scalable tracking of validation practices, adverse event reports, and post-market risk signals. Regulatory science might be the next major “LLM deployment” frontier. Read here: nature.com/articles/s4174…



Today, NSF announces the launch of the NSF Integrated Data Systems and Services program and the selection of 10 datasets for integration into the National Artificial Intelligence Research Resource Pilot to advance America's AI infrastructure. Learn more: bit.ly/4oW7ZxR

Excited to announce the SEA-AD DREAM on @SynapseOrg! Join the global research community to tackle AD using single cell data and innovative AI/ML solutions. Let’s accelerate discovery together! synapse.org/Synapse:syn664… @AllenInstitute @DR_E_A_M @Sagebio @SirotaLab @UCSF_BCHSI


With a contemporary smartphone, capturing, transmitting, and replicating sounds and visuals is a breeze, yet replicating scents remains elusive. If you want to change this, consider joining the 2025 @DR_E_A_M Olfaction Challenge at synapse.org/Synapse:syn647…. @jeriscience

FLI Team Achieves Success in International DREAM Challenge on Placental Aging. 🎉 Team ANTS from the @Leibniz_FLI in #Jena achieved second place in the global Placental Clock DREAM Challenge. 🥈 Congratulations! Read more: bit.ly/3D0Yf1L




A community effort to optimize sequence-based deep learning models of gene regulation go.nature.com/3NnblYZ

Paper is finally out! DREAM million promoter prediction challenge!

A community effort to optimize sequence-based deep learning models of gene regulation go.nature.com/3NnblYZ


