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This study introduces a computer-aided system for detecting ulcerative colitis, a chronic inflammatory bowel disease. The system can tell the various ulcer colitis severity levels by using a pre-trained deep learning model called EfficienetB2V3 and fine-tuning it on a special medical image dataset called LIMUC. This approach, known as transfer learning, improves the model’s accuracy by leveraging knowledge from a vast amount of data. The resulting system achieved 91% training accuracy in classifying ulcer colitis images and is designed to support healthcare providers in making earlier and more accurate ulcer colitis diagnoses.

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Ulcerative Colitis Diagnosis Through Efficient Net Transfer Learning

  • 会议论文

  • 发表日期：

    2025年

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  • Dharmendra Gupta,
  • Jayesh Gangrade,
  • Yadvendra Pratap Singh

摘要

This study introduces a computer-aided system for detecting ulcerative colitis, a chronic inflammatory bowel disease. The system can tell the various ulcer colitis severity levels by using a pre-trained deep learning model called EfficienetB2V3 and fine-tuning it on a special medical image dataset called LIMUC. This approach, known as transfer learning, improves the model’s accuracy by leveraging knowledge from a vast amount of data. The resulting system achieved 91% training accuracy in classifying ulcer colitis images and is designed to support healthcare providers in making earlier and more accurate ulcer colitis diagnoses.