https://github.com/ayax537/cancer_care_insight

The success of any project depends largely on the encouragement and guidelines of many others. We take this opportunity to express our gratitude to the people who have been instrumental in the successful completion of this project. The special thank goes to our helpful supervisor DR: Mary Mounir
https://github.com/ayax537/cancer_care_insight

Last synced: 30 days ago
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The success of any project depends largely on the encouragement and guidelines of many others. We take this opportunity to express our gratitude to the people who have been instrumental in the successful completion of this project. The special thank goes to our helpful supervisor DR: Mary Mounir

• Host: GitHub
• URL: https://github.com/ayax537/cancer_care_insight
• Owner: ayax537
• Created: 2024-11-05T07:51:31.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-11-05T07:58:40.000Z (about 2 months ago)
• Last Synced: 2024-11-05T08:33:48.811Z (about 2 months ago)
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Breast cancer is a type of cancer that originates in the cells of the breast. It

occurs when abnormal cells in the breast tissue begin to grow and divide

uncontrollably, forming a malignant tumor. Breast cancer can affect both women and

men, although it is much more common in women. Traditional classification use

morphology to divide tumors into separate categories with different behavior and

prognosis. However, there are limitations of traditional classification systems, and

new molecular methods are expected to improve classification systems. our website

dedicated to supporting doctors in the field of breast cancer. We provide valuable

resources and tools to aid medical professionals in their understanding and

management of this complex disease. In addition to conventional approaches, we

leverage the power of deep learning models to enhance diagnostic accuracy and

treatment planning. These models analyze vast amounts of data, enabling us to

extract meaningful insights and make informed decisions based on the

individualized characteristics of each patient's tumor. Our website offers a

comprehensive platform for doctors to access the latest research, clinical guidelines,

and innovative tools incorporating deep learning algorithms. By harnessing the

potential of these cutting-edge technologies, we aim to empower healthcare

professionals in their mission to provide the best possible care for breast cancer

patients. We already built a two successful models first model using CNN with

accuracy of 96% and second model using Random Forest with accuracy of 96%.