Detection of Pneumonia from Chest X-ray Images Utilizing MobileNet Model
Najran University · Chitkara University
Abstract
Pneumonia has been directly responsible for a huge number of deaths all across the globe. Pneumonia shares visual features with other respiratory diseases, such as tuberculosis, which can make it difficult to distinguish between them. Moreover, there is significant variability in the way chest X-ray images are acquired and processed, which can impact the quality and consistency of the images. This can make it challenging to develop robust algorithms that can accurately identify pneumonia in all types of images. Hence, there is a need to develop robust, data-driven algorithms that are trained on large, high-quality datasets and validated using a range of imaging techniques and expert radiological analysis. In…
Citation impact
- FWCI
- 43.74
- Percentile
- 100%
- References
- 36
Authors
7Topics & keywords
- Computer science
- Hyperparameter
- Artificial intelligence
- Pneumonia
- Consistency (knowledge bases)
- Deep learning
- Pattern recognition (psychology)
- Range (aeronautics)
- Good health and well-being