Artificial Intelligence-Assisted Diagnosis for Early Intervention Patients

The use of artificial intelligence to aid decision making is widely adopted today. Its application is found in different areas, among which the medical one is the most disruptive. However, there are few or no applications in Early Care that aid in the diagnosis and automatic assignment of therapy processes for children to help these centers. The objective of this work is to make a first approach to the problem and carry out a real proof of concept that demonstrates that this type of system can be useful in Early Care where the diagnosis and subsequent treatment must be determined by a multidisciplinary team. To measure the quality of the use of this type of technology, different machine learning techniques will be used on a real data set provided by the San Juan de Dios Hospital. This study will allow us to analyze the behavior of these techniques compared to traditional diagnosis. To make this comparison, there will be a qualified point of view in the field of children diagnosis.