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@article{201420,
        author = {Haritha A H and Mrs. Dhivya V M},
        title = {Lungs Disease Prediction Using Deep Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {no},
        pages = {113-116},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201420},
        abstract = {lung disease is one of the diseases that can be cured when the disease is spotted in its early stages before getting accumulated. But the most people fail to detect their disease before it comes to chronic. It leads to an increase in the death toll all around the world. Chest X-Ray is one of the most frequently used diagnostic modality in detecting different lung diseases such as pneumonia or tuberculosis. Also, deep learning techniques perform well in medical image classification tasks. This paper proposes a lung disease classification using lung x- ray image in 4 classes- pneumonia, tuberculosis, covid-19 and normal. The dataset is available in the public repository and can be freely download. The classification task is based on the transfer learning concept, it uses pre-trained algorithms for classification. In this implementation, make use of Resnet-50 algorithm for classification. It is one of the deeper neural networks. It performs well in many classification tasks. The algorithm extracts the features present in the input image in the dataset and use these features for learning, thereby, make predictions on new input X-ray images.},
        keywords = {Deep Neural Networks, Resnet-50, Transfer Learning.},
        month = {May},
        }