Taking precise, objective and rapid measurements of the midline shift of the brain is especially important in patients with traumatic brain injuries, as it is a decisive factor in making therapeutic decisions in a timely manner.

At DotProduct we develop a solution that quickly and with high precision reports the magnitude of the midline shift to treating physicians using brain CT scans and classical machine learning and computer vision techniques.

Within the framework of this project we have developed models and simulators with a high degree of automation and parameterization that may soon be incorporated into the fire management system used by the Uruguayan Society of Forestry Producers. These models, includes a modified version of FPI (fire potential index) and a fire simulator based on Cell2Fire but completly developed by us to fully control it behavor.

The aim of this system (under development) is to allow video capture of a child sitting on the lap of an adult. The video is processed to perform feature extractions and the different reactions to the stimuli are studied. Subsequently, these characteristics are used to discriminate children between the ones within the autism spectrum and and the neurotypical ones using artificial intelligence.

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