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Advancing Multimodal Medical Image Generation: A Self‐Improving Generative Foundation Model Click on the article title to read more.

#Highlight in #MedComm
Advancing Multimodal Medical Image Generation: A Self-Improving Generative Foundation Model doi.org/10.1002/mco2...

The highlighted article in @NatureMedicine : doi.org/10.1038/s415...

#BiomedicalEngineering #ComputationalModel #MedicalImaging

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A network analysis of digitized records from US conservative organizations in the 1920s through the 1950s shows that a previously unrecognized figure, Colby Chester, was at the center of early efforts to shrink government expansion. 

Image credit: Peter Roady.

A network analysis of digitized records from US conservative organizations in the 1920s through the 1950s shows that a previously unrecognized figure, Colby Chester, was at the center of early efforts to shrink government expansion. Image credit: Peter Roady.

Can #DataScience help historians mine new, valuable insights from a vast array of historical documents? A PNAS Science and Culture piece: www.pnas.org/doi/10.1073/...

#Digital #Historians #ComputationalModel #DigitalHistory #AI #NetworkAnalysis #LLMs

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#DecisionMaking #ComputationalModel #GameTheory #behavior #simulation #cooperation #organizations #prosocial #stayhome #SocialNorm #polarization #elections #turnout #mobilization

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By combining geospatial railway data with census data, historians explored the occupations of people living at different distances from tracks. The research, which used MapReader to train computer vision models to recognize features on digitized maps, shows that there were job opportunity upsides to living close to railroads. This map shows railspace (red squares) in East and Southeast London circa 1900. 

Image credit: Katherine McDonough.

By combining geospatial railway data with census data, historians explored the occupations of people living at different distances from tracks. The research, which used MapReader to train computer vision models to recognize features on digitized maps, shows that there were job opportunity upsides to living close to railroads. This map shows railspace (red squares) in East and Southeast London circa 1900. Image credit: Katherine McDonough.

Can #DataScience help historians mine new, valuable insights from a vast array of historical documents? A PNAS Science and Culture piece: www.pnas.org/doi/10.1073/...

#Digital #Historians #ComputationalModel #DigitalHistory #AI #NetworkAnalysis #LLMs

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A room filled with shelves of books. With data science tools in hand, historians can ask questions that would be difficult to answer with a lifetime of perusing tomes or scrolling through microfiche. Image credit: Shutterstock/BPTU.

A room filled with shelves of books. With data science tools in hand, historians can ask questions that would be difficult to answer with a lifetime of perusing tomes or scrolling through microfiche. Image credit: Shutterstock/BPTU.

Here’s how historians use #DataScience to mine the past in ways never before possible. A PNAS Science and Culture piece: www.pnas.org/doi/10.1073/... #Digital Historians #ComputationalModel #DigitalHistory #AI #NetworkAnalysis #LLMs

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Why do #substanceuse patterns often follow a U-shaped curve? A simple, theoretically grounded #computationalmodel simulates individual decisions and, for the first time, explains this population-level pattern.

Read #OpenAccess on #jasss: www.jasss.org/28/2/5.html

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Blue title card with white text "Davide Schaumann Intelligent Place Laboratory @ Technion" with the white Technion Israel Institute of Technology logo

Blue title card with white text "Davide Schaumann Intelligent Place Laboratory @ Technion" with the white Technion Israel Institute of Technology logo

📽️ In the latest #SONATA_horizon video we meet
Intelligent Place Laboratory at Technion, working on a #DigitalTwin and #ComputationalModel, developed to balance autonomous decision making with human intervention for healthier workspaces.

youtu.be/moEkQlMlMiA

#EuropeanCommission #HorizonEurope

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