The role of neural networks in predicting genetic risks and enhancing preventive health strategies

Advances in biotechnology and genetics allow more access to information regarding the genetic risk of individuals for diseases that affect them and their families. Genetic risks allow the planning of preventive health strategies and actions using different resources, such as predictive tests and genetic counseling. However, the amount of information raised is large and evolving, whereas traditional statistical methods have limitations. Artificial Intelligence and its neural networks have been used in different areas and have shown a surprising performance. These technologies have greater processing power than traditional computing. They can create models that emulate the functions of the human brain by identifying regularities in large data banks, both physical and health data, among others. And can predict with a certain level of precision what outcomes will or will not occur. The goal of this work is to hold some considerations about the implementation of neural networks in the prediction of genetic risks of diseases, and about these technologies and their potential in enhancing preventive health strategies. The efforts must be in developing strategies supporting the genetic counselors and health teams using AI tools and technology with neural networks for prediction at a population level, and preventive health actions and strategies with possible outcomes on the decrease of the transmissible risks and on improving the health conditions of families.