Treffer: Patient Prediction Through Convolutional Neural Networks.

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. [ABSTRACT FROM AUTHOR]

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