International Journal of Innovative Research in Computer and Communication Engineering

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TITLE Early Prediction of Lung Cancer Using Explainable AI Model
ABSTRACT Lung cancer remains a leading cause of death worldwide, largely because it's often diagnosed too late when treatment options become limited. While imaging technologies like chest X-rays and CT scans are crucial for detection, radiologists struggle with heavy workloads, fatigue, and inconsistencies in interpretation. This research presents Lung Vision, an intelligent system that uses deep learning to automatically analyze lung images while explaining its reasoning in ways doctors can trust and understand. The system combines image analysis with patient information (age, smoking history) to calculate a personalized cancer risk score, and crucially, it shows exactly which parts of the images triggered its alerts and why each factor matters. By bridging artificial intelligence with transparency, Lung Vision demonstrates how technology can genuinely assist physicians without replacing their expertise, offering a practical foundation for deploying trustworthy AI in real hospital environments. The system achieved strong detection accuracy (92–96%) while generating fast, interpretable results suitable for clinical workflow integration.
AUTHOR DR. SHIVAMURHTY R C, DR. AKSHATH M J, CHANDANA R, SUSHMITHA B R, N K CHANDANA, RADHIKA H P Department of Computer Science and Engineering, Maharaja Institute of Technology Mysore Affiliated to Visvesvaraya Technological University (VTU), Belagavi, Karnataka, India
VOLUME 177
DOI DOI: 10.15680/IJIRCCE.2025.1312157
PDF pdf/157_Early Prediction of Lung Cancer Using Explainable AI Model.pdf
KEYWORDS
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