An  Overview of Neutrosophic Theory in Medicine and Healthcare

Ahmed K. Essa; Ramiz Sabbagh; A. A. Salama; Huda E. Khalid; Abdul-Aziz A. Aziz; Ahmed A. Mohammed

Authors

Ahmed K. Essa Telafer University, Statistics Division, Telafer, Mosul, Iraq
Ramiz Sabbagh Telafer University, Department of the Scientific Affairs, Mosul, Iraq
A. A. Salama Department of Mathematics and Computer Science, Faculty of Science, Port Said University, Egypt
Huda E. Khalid Telafer University, The Administration Assistant for the President of the Telafer University, Telafer, Iraq
Abdul-Aziz A. Aziz Telafer University, President of the University, Telafer, Iraq
Ahmed A. Mohammed Telafer University, Manager of Construction and Projects Department, Telafer, Iraq

Keywords:

Neutrosophic logic, medical diagnosis, healthcare, neutrosophic sets, neutrosophic soft sets and lung disease diagnosis

Abstract

Neutrosophic ranking studies are an important part of medicine that determines the ranks of tests, risk factors, attributes, and medical suppliers. Neutrosophic clustering in healthcare can split data into groups (called clusters) to determine usage patterns for purposes, in which objects within the same cluster have similar properties and objects of different clusters have different properties.
Like neutrosophic clustering, neutrosophic classification studies are also a data mining technique. Neutrosophic pattern recognition is a machine learning process to decipher the underlying patterns in the concerned subjects. Neutrosophic time series analysis tries to find patterns and rules depending on time, neutrosophic recognition of medical images belongs to this type of study. This article comes as an attempt to review and shed light on almost all studies and subjects that used neutrosophic studies and algorithms related to medicine and healthcare for dozens of articles and authors