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Piramidal's foundation model for brain waves could supercharge EEGs | TechCrunch

Aug 27, 2024 - news.bensbites.com
Piramidal, a startup co-founded by Dimitris Sakellariou and Kris Pahuja, is developing an AI model to analyze brain scan data from electroencephalography (EEG) technology. The model aims to consistently identify worrying patterns in EEG data, regardless of the time, location, or type of equipment used. The co-founders believe this could improve outcomes for patients with brain disorders and alleviate some of the burden on healthcare professionals. The first production version of the model is set to be deployed in hospitals early next year, with four pilot tests planned in ICUs.

The company has secured a $6 million seed round co-led by Adverb Ventures and Lionheart Ventures, with participation from Y Combinator and angel investors. The funding will be used for compute costs and staffing. The company is also aggregating and harmonizing open-source EEG data to train their model. The partnerships with hospitals are expected to provide additional training data. The co-founders believe that their model, which they claim is the largest EEG model ever created, could eventually surpass human capability in identifying patterns in EEG data.

Key takeaways:

  • Piramidal, a startup co-founded by Dimitris Sakellariou and Kris Pahuja, is developing a foundational model for analyzing brain scan data, which could improve outcomes for patients with brain disorders and reduce workload for healthcare professionals.
  • The model aims to automate the analysis of electroencephalography (EEG) data, which is currently fragmented across different machines and requires specialized knowledge to interpret.
  • The first production version of the model is expected to be deployed in hospitals early next year, with four pilot programs planned to test the technology in intensive care units.
  • Piramidal has raised $6 million in seed funding from investors including Adverb Ventures and Lionheart Ventures, and is aggregating open source data to train its model.
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