Pneumonia
This dataset named "Chest X-ray images for Multiple diseases" is a medium sized dataset we collected and produced in 2024 from various sources to predict various Chest-X-ray diseases using Deep learning techniques, primarily from Radiopaedia.org, coronacases.org, Kaggle contains 1000 images for each of the disease namely TB,pneumonia,Covid-19,Normal. This dataset is designed to support the evaluation and development of algorithms to predict various chest x-ray diseases.
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Any damage that affects the normal functioning of the lungs is termed as a lung disease,
which can prove fatal if not detected early. To address this challenge, two innovative techniques proposed
for the lung disease classification, supporting medical professionals to diagnose and provides preventive
measures at an early stage. The proposed Model 1 integrates a custom MobileNetV2L2 architecture, that
builds upon the MobileNetV2 framework through fine-tuning and customization. This model incorporates a
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We prepared a new dataset (Cov-Pneum) for X-ray images by processing and merging three well-known publicly available datasets from Kaggle [1]–[4]. This dataset includes a total of 21,272 CXR images of COVID-19 (COVID-19 virus-infected lung), pneumonia (pneumonia-infected lung), and normal (clear lung) and consisting of images 4296, 5824, and 11152, respectively. We applied image scaling and preprocessing operations to enhance the quality of these CXR images.
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