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@article{174006,
        author = {ANUJ MOON and ARYAN BHAGAT and AYUSH RAMTEKE and TEJAS KARIYA and PROF. ANUJA GHASAD},
        title = {Implications of Detection pneumonia by using CNN and machine learning algorithms},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {2184-2188},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174006},
        abstract = {This project focuses on developing a deep learning model using Convolutional Neural Networks (CNNs) for the automated detection of pneumonia from chest X-ray images. Pneumonia remains a major global health concern, making early and precise diagnosis essential for effective treatment. The proposed CNN-based model aims to extract critical features from chest X-ray scans and classify them as pneumonia-positive or pneumonia- negative. A diverse dataset containing thousands of labeled chest X-ray images will be utilized, with data augmentation techniques incorporated to improve the model’s accuracy and robustness.},
        keywords = {Convolutional Neural Networks (CNN) in Medical Imaging Pneumonia Detection Using Deep Learning Chest X-ray Image Classification Automated Pneumonia Diagnosis CNN-Based Healthcare Solutions.},
        month = {March},
        }