For research in the field of neuroscience, Neurogram can significantly accelerate the investigation of these studies. Using state-of-the-art technology, we have developed algorithms capable of detecting differences that go beyond the range of human vision. This allows for more accurate and detailed analysis, providing valuable insights for advancing medical research.
In a study on focal cortical dysplasia conducted at the Brain Institute in Brazil, two genetically distinct groups were examined, which showed similar EEGs according to the neurophysiologists' analysis.
The Neurogram team pre-processed the data and used techniques for extracting features from brain waves to identify factors that could distinguish one group from the other.
After extracting these characteristics, the team trained a machine learning algorithm to test its ability to distinguish the two groups. The model successfully differentiated them with an accuracy of 83%, demonstrating that the groups were indeed distinct.
Researchers: Daniel Marinowic, Elaine Keiko Fujisao, Daniele G. De Mari, and John Johnson
