Current Volume 9
AI-Assisted Early Detection of Oral Cancer Using Attention-Guided Deep Learning and Automated Diagnostic Reporting
Abstract
Late-stage oral cancer diagnosis is a problem we have had the tools to address for years — the bottleneck has always been getting those tools into the right hands fast enough. Our work grew out of that frustration. We put together AGMSFFNet, a histopathology classifier that pairs a modified EfficientNet-B5 backbone with a dual-branch attention design we call HSCA, which handles both spatial and channel recalibration at once. Alongside that, multi-resolution LBP texture descriptors feed into the feature pipeline to capture detail that convolution alone tends to skip over. The part we are most invested in, though, is the LangGraph reporting layer — rather than stopping at a class label, the system drafts a structured clinical summary automatically, flags anything it is uncertain about, and hands a readable report to the pathologist. Testing on ORCHID gave us 98.7% accuracy, 98.9% precision, 98.5% recall, and a 98.7% F1. External results on NDBUFES held up at 97.5%. ANOVA and Tukey tests confirmed the differences were statistically meaningful.
Keywords
Oral Cancer Classification, Deep Learning, Efficientnet, Attention Mechanisms, Feature Fusion, Histopathological Image Analysis, Langgraph, Agentic AI, Interpretable AI.
Citations
IRE Journals:
Sneha Sawant, Lokesh Thakare, Mushfiq Shaikh, Suhas Waghmare "AI-Assisted Early Detection of Oral Cancer Using Attention-Guided Deep Learning and Automated Diagnostic Reporting" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 2577-2580 https://doi.org/10.64388/IREV9I10-1716822
IEEE:
Sneha Sawant, Lokesh Thakare, Mushfiq Shaikh, Suhas Waghmare
"AI-Assisted Early Detection of Oral Cancer Using Attention-Guided Deep Learning and Automated Diagnostic Reporting" Iconic Research And Engineering Journals, 9(10) https://doi.org/10.64388/IREV9I10-1716822
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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