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@article{174582,
        author = {K.Siva Venkata Naga Sai and Mr.M.V.RamaMurthy and K.Praveen and K.Dhanush Naidu and T.Sai Sri Sindhu},
        title = {Interactive Platform for Brain Tumor Detection Using CNN Model},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {331-336},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174582},
        abstract = {The primary objective of our project is to develop an advanced brain tumor detection system using convolutional neural networks (CNNs) to assist in the early diagnosis of brain tumors. With the increasing prevalence of brain tumors, early detection plays a crucial role in improving patient outcomes. Traditional diagnostic methods often require extensive expertise and time, leading to delays in diagnosis. Our automated system analyzes MRI scans to detect brain tumors with high accuracy, significantly reducing the reliance on manual interpretation. By utilizing deep learning algorithms, the system can differentiate between tumor and non-tumor images, providing accurate and timely results. The proposed model, integrated with a user-friendly interface, ensures accessibility for medical practitioners, aiding in quicker decision-making. Unlike conventional diagnostic approaches, our solution minimizes the margin of error and enhances diagnostic confidence. The ultimate aim of this project is to offer a reliable and efficient tool for medical professionals, contributing to the advancement of medical diagnostics and the early detection of brain tumors for improved patient care.},
        keywords = {Brain tumor detection, convolutional neural networks (VGG16), Django, medical image analysis, MRI scan classification, deep learning in healthcare, image processing, computer-aided diagnosis, medical diagnostics, healthcare AI, tumor identification.},
        month = {March},
        }