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Researchers at the Autonomous University of Zacatecas are working on developing software to detect a person's susceptibility to developing dental caries without having to open their mouths and to reduce investments in economic and human resources. the field of oral health, to perform this activity, because it will be enough to answer a questionnaire of 10 to 13 questions and the computer program will take care of the rest.
According to a report of the National Council of Science and Technology (Conacyt) This project, which runs since 2017, is focused on the infant population and is developed by the dental surgeon, Nubia Maricela Chávez Lamas, in collaboration with the doctor, Carlos Eric Galván Tejada, research professor at the Academic Unit of Software Engineering, and the student of the Master of Science in Engineering, Laura Alejandra Zanella Calzada, fellow of the Conacyt.
This software works through what is called machine learning, where the developer tells the system to perform certain actions depending on what is happening in the environment, this without having to handle it constantly and in this case, the model measures two determinants of health, which are the socio-economic and nutritional conditions of the person to finally identify the predisposition of children or the general population to suffer from caries through a set of data and machine learning algorithms that feed a deep neural network that will determine whether or not the patient can have cavities. (By Víctor Montes Rentería / Photo: Conacyt)
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