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Patient Prediction Through Convolutional Neural Networks Cover

Patient Prediction Through Convolutional Neural Networks

Open Access
|Dec 2022

Abstract

This paper presents a methodology for predicting the lung diseases of patients through medical images using the Convolutional neural network (CNN). The importance of this work comes from the current SARS-CoV-2 pandemic simulation where with the presented method in this work, pneumonia infection from healthy situation can be diagnosed using the X-ray images. For validating the presented method, various X-ray images are employed in the Python coding environment where various libraries are used: TensorFlow for tensor operations, Scikit-learn for machine learning (ML), Keras for artificial neural network (ANN), matplotlib and seaborn libraries to perform exploratory data analysis on the data set and to evaluate the results visually. The practical simulation results reveal 91% accuracy, 90% precision, and 96% sensitivity making prediction between diseases.

Language: English
Page range: 52 - 56
Published on: Dec 12, 2022
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2022 Cagatay Sunal, Lida Kouhalvandi, published by University of Medicine, Pharmacy, Science and Technology of Targu Mures
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.