| Abstract |
The medical field is currently experiencing a revolutionary phase propelled by Artificial Intelligence (AI). Progress in digital data collection, machine learning algorithms, and robust computing infrastructure has broadened the scope of AI applications into domains traditionally handled exclusively by human experts. Brain tumors, characterized by abnormal tissue growth from uncontrolled cell division, present significant health risks due to their potential malignancy. These tumors can invade and damage healthy brain tissue, posing life-threatening consequences. This project explores recent advancements in AI technology and their applications in biomedical sciences. We identify challenges that must be overcome to advance medical AI systems and examine the economic, legal, and social implications of integrating AI into healthcare.
Addressing this urgent need, we propose an innovative approach for precise brain tumor detection and classification. Our project introduces a user-friendly interface designed to facilitate tumor detection, classification, and visualization of severity. This system harnesses Convolutional Neural Networks (CNNs) to achieve robust tumor classification and integrates state-of-the-art machine learning algorithms to enhance performance
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