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Revisiting the utility of identifying nuclear grooves as unique nuclear changes by an object detector model.

Pedro R F RendeJoel Machado PiresKátia Sakimi NakadairaSara LopesJoão ValeFabio HechtFabyan E L BeltrãoGabriel J R MachadoEdna T KimuraCatarina EloyHelton E Ramos
Published in: Journal of pathology and translational medicine (2024)
The model was able to develop a structure predictor rule, indicating that the application of an artificial intelligence model based on object detection in the identification of nuclear grooves is feasible. Associated with a reduction in interobserver variability and in time per slide, this demonstrates that nuclear evaluation constitutes one of the possibilities for refining the diagnosis through computational models.
Keyphrases
  • artificial intelligence
  • machine learning
  • working memory
  • deep learning
  • magnetic resonance imaging
  • magnetic resonance
  • monte carlo