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This paper introduces "NeuroScan-Brain Tumor Detection Using CNN," a groundbreaking project integrating Convolutional Neural Networks (CNNs) for early brain tumor diagnosis via MRI image analysis. With deep learning's burgeoning influence, CNNs emerge as potent tools for healthcare challenges. Brain tumors, with their dire implications, necessitate swift and accurate diagnosis for effective intervention. Automated CNN-based analysis overcomes manual classification limitations, promising improved patient outcomes. Building on successful CNN-based detection, this project innovatively integrates geolocation services, pinpointing patients' locations post-detection to expedite access to nearby specialist care. By harmonizing AI with geolocation, NeuroScan streamlines specialized healthcare access, potentially curbing brain tumor mortality. Employing advanced CNN architectures, NeuroScan achieves efficient tumor detection, utilizing fewer features than traditional methods. This multidisciplinary strategy is a big step forward in using technology to improve patient care and healthcare delivery. Key Words: : Convolutional Neural Networks, Brain tumors, geolocation services, CNN architectures.
Nikhil Kumar (Mon,) studied this question.
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