Data mining of a group of diseases

سال انتشار: 1403
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 132

فایل این مقاله در 11 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

CARSE08_314

تاریخ نمایه سازی: 10 دی 1403

چکیده مقاله:

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 ۱۹۶۰s, 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 ۱۹۹۰. 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.

نویسندگان

Shabnam Zarghami

Ph.D. Student, Department of Mathematics, University of Qom, Qom, Iran

Gholam Hassan Shirdel

Associate Professor, Department of Mathematics, University of Qom, Qom, Iran

Mojtaba Ghanbari

Assistant Professor, Department of Mathematics, Farahan Azad University, Farahan City, Iran

Mohammad Reza Eskandari

Neurology and Psychiatry Subspecialist, Harvard University, USA