Smart Neuro-Oncology Assistant: A Chatbot for Brain Tumour Detection and Primary Cancer Prediction
Year: 2025
Type: article
Abstract: The Smart Neuro-Oncology Assistant introduces a novel AI-powered platform that combines deep learning-based brain tumor detection with primary cancer prediction capabilities, particularly for tumors associated with Glioma and Pituitary regions. This interactive system supports patients and healthcare professionals throughout the neuro-oncological assessment process. Utilizing the Xception convolutional neural network architecture, the system achieves 96% overall accuracy in classifying brain MRI scans into four categories: Glioma, Meningioma, Pituitary Tumor, and No Tumor. The platform extends beyond basic classification by evaluating cancer likelihood and delivering personalized guidance through an interactive chatbot powered by Google's Gemini 1.5 Flash generative AI model. Key features include secure user authentication, robust image validation, specialist recommendations based on detected tumor types, and comprehensive historical data tracking for longitudinal assessment. Developed using Streamlit for the frontend interface, Flask for backend services, and MongoDB for efficient data management, the system demonstrates exceptional performance with class-specific F1-scores ranging from 0.93 to 0.98. This research contributes to AI-assisted medical diagnostics by promoting a human-centered approach that supports clinical expertise, aiming to streamline diagnostics and enhance patient understanding in neuro-oncology.
Author: Kartik Deogire
Language: English
Subfield: Neurology
Field: Neuroscience
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4409593184