hallowshaw/Lung-Cancer-Prediction-using-CNN-and-Transfer-Learning

A deep learning-based system for predicting lung cancer from CT scan images using Convolutional Neural Networks (CNN). This project utilizes the Xception model for image classification into four categories: Normal, Adenocarcinoma, Large Cell Carcinoma, and Squamous Cell Carcinoma.

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This project offers a deep learning system to help medical professionals classify lung cancer from CT scan images. By inputting chest CT scans, the system outputs a classification into one of four categories: Normal, Adenocarcinoma, Large Cell Carcinoma, or Squamous Cell Carcinoma. It's designed for radiologists, oncologists, or pathology labs seeking automated preliminary image analysis.

No commits in the last 6 months.

Use this if you need an automated tool to help categorize lung cancer types from medical images for diagnostic support or research.

Not ideal if you require a certified medical device for direct clinical decision-making without expert human oversight.

radiology oncology medical-imaging cancer-detection pathology
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 16 / 25

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43

Forks

8

Language

Jupyter Notebook

License

MIT

Last pushed

Jul 01, 2024

Commits (30d)

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