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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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Issue: October 2025
Volume 10 | Issue 10
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 113
Article Submitted : 18099
Article Published : 7764
Total Authors : 20527
Total Reviewer : 747
Total Countries : 142
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Published Paper Details
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| Paper Title: | Early Detection Of Intrahepatic Duct Cancer Using Deep Learning Techniques |
| Authors Name: | M. Rajasekar , Dr. D. Karthikeyan , A. Sakthi Ramana , C. Saravanan , R. Vijay |
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IJRTI_203627
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| Published Paper Id: | IJRTI2505092 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | Bile duct cancer is a rare and aggressive malignancy with a poor prognosis due to late diagnosis. Early detection is crucial for improved treatment outcomes. This study investigates the potential of a deep learning approach, specifically a CNN architecture, for the early detection of bile duct cancer from medical images. The proposed system utilizes a pre-trained Inception model, fine-tuned on a dataset of medical images (e.g., endoscopic images, CT scans, MRI scans) annotated with bile duct cancer presence or absence. The CNN architecture effectively extracts relevant features from the images, enhancing the model's ability to identify subtle patterns indicative of malignancy. Preliminary results demonstrate promising accuracy in classifying images as cancerous or non-cancerous. The CNN model shows potential to assist clinicians in early diagnosis, enabling timely intervention and potentially improving patient survival rates. |
| Keywords: | Bile duct cancer, Python, Deep Learning, Convolution Neural Network. |
| Cite Article: | "Early Detection Of Intrahepatic Duct Cancer Using Deep Learning Techniques ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.a786-a791, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505092.pdf |
| Downloads: | 000239 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2505092
Registration ID:203627
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: a786-a791 Country: Perambalur , Tamilnadu , India Research Area: Bio Medical Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505092 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505092 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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