Volume 15, Issue 1 · IJARST · ISSN 2319-1783 / 2320-1126

Web-Integrated AI System for Bone Cancer Prediction

Web-Integrated AI System for Bone Cancer Prediction is an open-access, peer-reviewed research paper by Pradeep Rao K B, Ganavi G, Harshitha L, Manvi H J and Pavan J, published in Volume 15, Issue 1 of the International Journal of Advanced Research in Science and Technology (IJARST), a UGC-approved journal (Print ISSN 2319-1783, Online ISSN 2320-1126).

Author

Pradeep Rao K B, Ganavi G, Harshitha L, Manvi H J and Pavan J

Abstract

Bone cancer detection from X-ray images is challenging due to subtle tumor characteristics, radiologist fatigue, and limited access to specialized expertise, particularly in resource-constrained settings. Early and accurate diagnosis is critical for improving patient outcomes. However, conventional methods rely heavily on manual interpretation, leading to delays and variability. This study proposes a web-integrated AI system for automated bone cancer prediction using deep learning. The system employs the EfficientNet-B0 architecture with transfer learning to classify bone X-ray images as normal or cancerous, supported by preprocessing, data augmentation, and class-weighting techniques to address data scarcity and class imbalance. The trained model is deployed as a user-friendly web application enabling X-ray upload, report generation, scan history management, and interaction through an integrated AI chatbot. The proposed system aims to provide an efficient, interpretable, and clinically supportive diagnostic tool for early bone cancer detection.

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DOI

10.62226/ijarst20262604

PAGES : 1766-1771 | 6 VIEWS | 5 DOWNLOADS

How do you cite this paper?

Pradeep Rao K B, Ganavi G, Harshitha L, Manvi H J and Pavan J — “Web-Integrated AI System for Bone Cancer Prediction.” International Journal of Advanced Research in Science and Technology (IJARST), Volume 15, Issue 1. DOI: 10.62226/ijarst20262604.

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