Data mining of a group of diseases

Background and Aim : Data mining is one of the stages of acquiring knowledge in a database to collect useful information. Data mining is a new field that has various applications and it is known as one of the top ten sciences affecting technology. Data mining analyzes databases and massive data sets in order to discover and extract knowledge, and machine (and semi-machine) mines. Such studies and explorations can actually be considered the extension and continuation of the ancient and ubiquitous knowledge of statistics. The major difference is the scale, breadth and variety of fields and applications, as well as the dimensions and sizes of today's data, which require machine learning, modeling, and training methods. In the 1960s, statisticians used the term "Data Fishing" or "Data Dredging" to discover any relationship in a very large volume of data without considering any assumptions. After thirty years and with the accumulation of data in databases, the term "Data Mining" became more popular around 1990. The purpose of this research is to predict brain and nerve diseases using data mining algorithms. The purpose of this research is to help medical professionals to predict disease.In this research, we used different meters such as Manhattan, cosine similarity, Pearson, Minkowski and K nearest neighbor and implemented a program to predict neurological diseases.

Data mining of a group of diseases Keywords:

treatment methods , data mining , prediction of diseases , diseases