A Comprehensive review of Recent Advances for detection of Covid-19 and Pneumonia for Chest X-Rays using Deep Learning.

Global pandemic due to Covid-19 has propelled research in Artificial Intelligence for detection and management of diseases. This paper presents survey on different techniques applied to diagnose, detect and monitor Covid-19, Pneumonia and many other lung diseases. The study characterizes the existing approaches based on different techniques using different data types, medical imaging, clinical data and time series data. A detailed comparative analysis of various models such as Convolutional Neural Networks (CNNs), LSTM networks, Deep learning methods and Ensemble learning methods is provided. Further, this paper highlights the gaps and key challenges such as limited datasets, lacks dataset diversity, lacks generalization and ethical concerns. Also, this paper presents the proposed methodology in which various techniques like Discrete Wavelet Transformation (DWT), Radial Basis function Neural Network(RBFNN), CNN and SVM. This survey aims to provide the researchers in detailed comparison of techniques used for identifying, detecting and monitoring of COVID-19 and other lung diseases. Also, future research directions are discussed for creation of models to enhance generalization utilizing varied datasets.