Lung Cancer Diagnostician

[Mayur3sh007]

🔴 Project Title : Lung Cancer Detection Using CT Scans

🔴 Aim : To develop a machine learning model for detecting lung nodules indicative of lung cancer from CT scan images.

🔴 Dataset : https://www.kaggle.com/datasets/fanbyprinciple/luna-lung-cancer-dataset

🔴 Approach :

• Exploratory Data Analysis (EDA):

  • Perform EDA to understand the dataset: load the LUNA16 dataset, explore image distributions, visualize sample CT scan images, and preprocess images (resize, normalize).

• Model Selection and Comparison:

  • Implement and compare 3-4 algorithms: Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), Random Forests (RF), and Logistic Regression (LR).
  • Train each model on the dataset, tune hyperparameters, and evaluate using metrics like accuracy, precision, recall, F1-score, and possibly AUC-ROC.

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📍 Follow the Guidelines to Contribute to the Project :

• You need to create a separate folder named as the Project Title.
• Inside that folder, there will be four main components:
  • Images - To store the required images.
  • Dataset - To store the dataset or information/source about the dataset.
  • Model - To store the machine learning model you've created using the dataset.
  • requirements.txt - This file will contain the required packages/libraries to run the project on other machines.
• Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

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🔴🟡 Points to Note :

• The issues will be assigned on a first-come, first-served basis, 1 Issue == 1 PR.
• "Issue Title" and "PR Title should be the same. Include issue number along with it.
• Follow Contributing Guidelines & Code of Conduct before starting to contribute.

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✅ To be Mentioned while taking the issue :

• Full name : Mayuresh Chavan
• GitHub Profile Link : https://github.com/Mayur3sh007)](https://github.com/Mayur3sh007
• Participant ID (If not, then put NA) : NA
• Approach for this Project : Perform exploratory data analysis (EDA) to understand the LUNA16 dataset, including image preprocessing. Implement and compare Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), Random Forests (RF), and Logistic Regression (LR) for lung nodule detection. Evaluate models using accuracy, precision, recall, and F1-score metrics. Document findings and conclusions in the README.md under the Model folder.
• What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.) : VSOC

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Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

[github-actions]

Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊

[Mayur3sh007]

I am a contributor from VSOC, assign me this issue @Mayur3sh007

[abhisheks008]

Can you implement 6-7 models for this project?

[Mayur3sh007]

Yeah sure

[abhisheks008]

Assigned @Mayur3sh007

[Sanjanah8]

Can u assign this to me as well

[abhisheks008]

Can u assign this to me as well

Can you please share your approach for this issue?

[Sanjanah8]

Can u assign this to me as well

Can you please share your approach for this issue?

Starting with exploratory data analysis,computer neural networks(CNN) for image classification ,other ML models for a basic layout about the features

[abhisheks008]

Can u assign this to me as well

Can you please share your approach for this issue?

Starting with exploratory data analysis,computer neural networks(CNN) for image classification ,other ML models for a basic layout about the features

Please be specific with the models you are planning to implement. Mention at least 6-7 models for taking any issue.

[Sanjanah8]

Can u assign this to me as well

Can you please share your approach for this issue?

Starting with exploratory data analysis,computer neural networks(CNN) for image classification ,other ML models for a basic layout about the features

Please be specific with the models you are planning to implement. Mention at least 6-7 models for taking any issue.

Cnn, random forest,xg boost, logistic regression ,svm,knn or naive bayes

[Sanjanah8]

Can u assign me to any one of the projects so that I can start working because ssoc is coming to its end

[abhisheks008]

Can u assign me to any one of the projects so that I can start working because ssoc is coming to its end

Assigned @Sanjanah8. Please make sure that you implement all the mentioned models as per your approach.