Discover and read the best of Twitter Threads about #AIforHealth

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I'm excited to share that our work on SARS-CoV-2 is now published in @NatureChemistry! I'm humbled to have led this effort and provide a brief summary below: nature.com/articles/s4155…
Millions of @foldingathome users pooled their resources to create the first #Exascale computer and generated the world's largest MD dataset, simulating nearly the entire SARS-CoV-2 proteome.
We were the first group to discover that the Spike protein has incredible conformational heterogeneity and can adopt an 'open' state that reveals many cryptic epitopes. Many nAbs have since been found to target these cryptic epitopes!
Read 13 tweets
🚨#COVID19 PAPER ALERT🚨
With your help, F@h became the first #exascale computer, collected 100,000X more data than a normal paper, learned how the #Demogorgon evades our immune system, and discovered drug targets called ‘cryptic’ pockets (#FAHPockets)!
biorxiv.org/content/10.110…
With over a million people downloading F@h, we reached #exascale computing speed within weeks. This made us >5X faster than the IBM Summit supercomputer, the fastest traditional supercomputer in the world!
This newfound power enabled us to simulate every possible protein from the #SARSCoV2 virus in parallel. Together, we generated the largest dataset of protein dynamics in history. We’ve highlighted some of our exciting findings in this thread:
Read 14 tweets
#BREAKING: Researchers from @IHME_UW find demand for beds in US hospital intensive care units is likely to far exceed capacity for #COVID19 patients as early as the second week of April. Press release➡️bit.ly/IHME-COVID19
“The trajectory of the (#COVID19) pandemic will change – and dramatically for the worse – if people ease up on social distancing or relax with other precautions,” said Dr. Christopher Murray, Director of @IHME_UW.
Health systems can help address excess #COVID19 demand by:

✅Postponing elective procedures
✅Increasing # of beds above licensed capacity
✅Establishing emergency field hospitals
✅Reducing staff-to-patient ratios.
Read 13 tweets

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