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Cervical Cancer Prediction and Classification Using Deep Learning on Medical Image Data | Python

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Cervical Cancer Prediction and Classification Using Deep Learning on Medical Image Data | Python Final Year IEEE Project 2024 - 2025.
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📌Our Proposed Project Title: Cervical Cancer Prediction and Classification Using Deep Learning on Medical Image Data.
💡Implementation: Python.
🔬Algorithm / Model Used: Xception Architecture.
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.5000/
📘Project Abstract:
Cervical cancer is one of the leading causes of cancer-related deaths among women worldwide. Cervical cancer remains a significant global health challenge, with early detection being pivotal for reducing mortality rates. Early and accurate detection is critical for effective treatment and improved survival rates. This project, titled "Cervical Cancer Prediction and Classification Using Deep Learning on Medical Image Data," aims to leverage advanced deep learning techniques for automated and precise classification of cervical cancer stages using medical images.
🚀IEEE Base Paper Title: A Novel Web Framework for Cervical Cancer Detection System: A Machine Learning Breakthrough.
📍REFERENCE:
MIMONAH AL QATHRADY, AHMAD SHAF, TARIQ ALI, UMAR FAROOQ, AQIB REHMAN, SAMAR M. ALQHTANI, MOHAMMED S. ALSHEHRI, SULTAN ALMAKDI, MUHAMMAD IRFAN, SAIFUR RAHMAN, AND LADON AHMED BADE ELJAK, “A Novel Web Framework for Cervical Cancer Detection System: A Machine Learning Breakthrough”, in IEEE Access, vol. 12, pp. 41542-41556, 2024.
❓Frequently Asked Questions:
1. What is the primary purpose of this project?
2. What dataset is used in this project?
3. Which deep learning architecture is used in this system?
4. What is the achieved accuracy of the system?
5. What tools and technologies were used to develop this project?
6. How does the system work?
7. Who can use this system?
8. Does this system require high-end hardware?
9. How does this project differ from the existing system?
10. What challenges does this system address?
11. How is the user experience optimized?
12. What are the limitations of this system?
🏷️tags:
#cervicalcancer #python #pythonprojects #ieeeprojects #ml #aiproject #ai #cancerpredictions #machinelearningproject #pythonprogramming #pythonprojectforbeginners #pythonprojectideas #pythonmachinelearning #machinelearning #machinelearningpython #finalyearproject #ieeeprojects #finalyearprojects #datascience #datascienceproject #artificialintelligenceproject #projects #deeplearning #deeplearningproject #computerscienceproject #deeplearningprojects #majorprojects #academicprojects #majorproject
(or)
To buy this project in ONLINE, Contact:
📌Our Proposed Project Title: Cervical Cancer Prediction and Classification Using Deep Learning on Medical Image Data.
💡Implementation: Python.
🔬Algorithm / Model Used: Xception Architecture.
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.5000/
📘Project Abstract:
Cervical cancer is one of the leading causes of cancer-related deaths among women worldwide. Cervical cancer remains a significant global health challenge, with early detection being pivotal for reducing mortality rates. Early and accurate detection is critical for effective treatment and improved survival rates. This project, titled "Cervical Cancer Prediction and Classification Using Deep Learning on Medical Image Data," aims to leverage advanced deep learning techniques for automated and precise classification of cervical cancer stages using medical images.
🚀IEEE Base Paper Title: A Novel Web Framework for Cervical Cancer Detection System: A Machine Learning Breakthrough.
📍REFERENCE:
MIMONAH AL QATHRADY, AHMAD SHAF, TARIQ ALI, UMAR FAROOQ, AQIB REHMAN, SAMAR M. ALQHTANI, MOHAMMED S. ALSHEHRI, SULTAN ALMAKDI, MUHAMMAD IRFAN, SAIFUR RAHMAN, AND LADON AHMED BADE ELJAK, “A Novel Web Framework for Cervical Cancer Detection System: A Machine Learning Breakthrough”, in IEEE Access, vol. 12, pp. 41542-41556, 2024.
❓Frequently Asked Questions:
1. What is the primary purpose of this project?
2. What dataset is used in this project?
3. Which deep learning architecture is used in this system?
4. What is the achieved accuracy of the system?
5. What tools and technologies were used to develop this project?
6. How does the system work?
7. Who can use this system?
8. Does this system require high-end hardware?
9. How does this project differ from the existing system?
10. What challenges does this system address?
11. How is the user experience optimized?
12. What are the limitations of this system?
🏷️tags:
#cervicalcancer #python #pythonprojects #ieeeprojects #ml #aiproject #ai #cancerpredictions #machinelearningproject #pythonprogramming #pythonprojectforbeginners #pythonprojectideas #pythonmachinelearning #machinelearning #machinelearningpython #finalyearproject #ieeeprojects #finalyearprojects #datascience #datascienceproject #artificialintelligenceproject #projects #deeplearning #deeplearningproject #computerscienceproject #deeplearningprojects #majorprojects #academicprojects #majorproject