Esophageal Cancer Prediction System using Deep Learning Yolo V11 Model

Author(s)	Prof. A. Lavanya M.E., Shiyamala Devi G, Sofiya S, Sushma R
Country	India
Abstract	Esophageal Cancer Detection System using YOLOv11 aims to improve early diagnosis by automatically detecting cancerous regions in medical images. Using the YOLOv11 deep learning model, trained with machine learning techniques, this system quickly and accurately identifies esophageal cancer, even in its early stages. By analyzing images such as endoscopies and CT scans, it highlights suspicious areas and provides cancer probabilities, aiding clinicians in making better-informed decisions and ultimately improving patient outcomes.
Keywords	Esophageal cancer, deep learning, YOLO v11, tumor detection, medical imaging, real-time diagnosis, AI-assisted healthcare, endoscopic images, FastAPI, React frontend, model evaluation, Grad-CAM, data preprocessing, hyperspectral imaging, automated reporting, healthcare analytics.
Field	Medical / Pharmacy
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-03-26
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.39866
Short DOI	https://doi.org/g892pj

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International Journal For Multidisciplinary Research