Deep And Machine Learning Towards Pneumonia And Asthma Detection
Amani Yahyaoui, Nejat Yumuşak
Abstract
Machine Learning is a branch of artificial intelligence widely used in the medical field to analyze high-dimensional medical data and the early detection of certain dangerous diseases. Lung diseases continue to increase the mortality rate in the world. The early and accurate prediction of lung diseases has become a primary necessity to save patient's lives and facilitate doctor's works. This paper focuses on predicting certain chest diseases such as Pneumonia and Asthma using Deep Learning (DL) and Machine Learning (ML) techniques, respectively, the Deep Neural Network (DNN), and the K-nearest Neighbors (KNN) methods. These approaches are evaluated using a private data set from the pulmonary diseases department of Diyarbakir hospital, Turkey. It consists of 212 samples, 38 input characteristics characterize each one. The results obtained showed the effectiveness of these methods to detect pulmonary diseases, particularly the KNN, by giving a detection accuracy of 95% and 94.3% by using the DNN method.