Özet:

Abstract Infectious agents such as bacteria, viruses, and fungi may all lead to a lung infection known as pneumonia. Particularly at risk are the elderly and those with weak immune systems, but anybody may fall victim to this potentially fatal sickness. Several investigations have used deep learning and machine learning strategies to identify pneumonia in chest X-rays and CT scans. Using these methods, a model is trained on a huge collection of labelled photos so that it can recognise characteristics and patterns characteristic of pneumonia. In 2017, for instance, the journal Radiology included a research that employed deep learning to diagnose pneumonia. With an AUC (area under the curve) of 0.97, this study's authors reported that a convolutional neural network (CNN) trained on a dataset of chest X-rays could effectively categorise pictures as normal or pneumonia. Another research that employed a machine learning technique to diagnose pneumonia from chest X-rays was published in 2018 in the journal Chest. Researchers discovered that their model had an AUC of 0.94 and an 89.6 percent success rate. The application of deep learning and machine learning to diagnose pneumonia has shown encouraging results so far, and it has the potential to improve diagnostic precision and productivity.

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