Artificial Intelligence-Based Pneumonia Detection via Chest X-Ray – A State-of-the-Art Review
Keywords:Artificial intelligence, pneumonia, chest X-ray, machine learning, deep learning, transfer learning, state-of-the-art
Artificial intelligence (AI) has emerged as a useful tool for early detection of pneumonia disease in the lungs using chest X-ray (CXR). For pneumonia detection different machine learning, deep learning, and transfer learning algorithms are used but a detailed review comparing the dataset with literature is lacking. This review paper first briefly summarizes different AI-based algorithms on classification, regression, and clustering. Then a detailed comparison of current literature on the ground of different reliable datasets and techniques are presented. Lastly, major challenges faced over the last few years are discussed with their future scopes. Our main objective is to provide a state-of-the-art review of the AI studies detecting pneumonia disease in CXR using data comparison and find the limitations to make suggestions for practitioners.
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