Survey for Lung diseases using machine learning methods

Eman Hamid Hadi; Hussein Attya Lafta; Sura Z. Al-Rashid

doi:10.53730/ijhs.v6nS3.6887

Authors

Eman Hamid Hadi
aeminhmed@gmail.com
College for Women, University of Babylon, Babylon, Iraq
Hussein Attya Lafta Hussein Attya Lafta works at College of Information Technology, University of Babylon, Babylon, Iraq
Sura Z. Al-Rashid College of Information Technology, University of Babylon, Babylon, Iraq

Keywords:

COVID-19, CNN, genetic expression, deep learning, machine learning

Abstract

Recent developments in artificial intelligence and machine learning are of great importance in supporting, identifying, and classifying Lung diseases, whether using medical images or using gene expression. That is why many researchers have worked to detect lung diseases using various methods of machine learning. This paper presents a survey of 20 papers using different methods. To screen for lung disease. And the goal From this paper present a classification of the latest lung diseases based on machine learning. Classification consists of a number of features common to the surveys are: Types of data used, types of lung diseases, types of machine learning algorithms used, and this classification is of great importance and can be used by many researchers to plan their contributions and research activities in many fields. It is also important in terms of improving the efficiency and accuracy of machine learning in examining and classifying lung diseases with the least possible error.

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