The spinal cord plays a critical role in transmitting sensory and motor signals between the brain and body. Disorders such as herniated discs, fractures, and nerve compressions remain difficult to detect accurately using only traditional diagnostic tools like X-rays and MRI scans. This study proposes an AI-based spinal cord detection system powered by Convolutional Neural Networks CNNs to localize pain regions and provide preliminary treatment suggestions. The system shows higher diagnostic accuracy, faster processing, and significant clinical support compared to conventional radiology practices. The experimental evaluation demonstrates improved accuracy and reduced diagnostic time, highlighting the potential of AI integration in spinal care.