Breast cancer is the fifth largest cause of death globally, with 0.68 million deaths and 2.3 million cases, 90,000 cases, and 40,000 deaths in Pakistan alone. There are about 200 million tests conducted globally. Early diagnostics of cancer increases the chance of survival significantly.The stimulus
early detection of breast tumor using machine learning techniques
Breast cancer is the fifth largest cause of death globally, with 0.68 million deaths and 2.3 million cases, 90,000 cases, and 40,000 deaths in Pakistan alone. There are about 200 million tests conducted globally. Early diagnostics of cancer increases the chance of survival significantly.The stimulus of a tumor can be ignored by the naked eye but not with the computerized method, which focuses on a pixel level. There is a rise in automation of industries through the implementation of artificial intelligence as it is proven to be faster, accurate, and precise with no human influence like emotion, mood or stress. This research is based on the improving accuracy of tumor detecting machine learning models by exploring different techniques and performing a fair comparison. It covers the implementation of different image retrieval techniques.
- Improving accuracy, AUC w.r.t existing models
- Training on an enhanced dataset
- Explore different techniques in various languages and compare their performance.
1)Introduction of patch-based ML techniques, fitted on multiple scales. extraction of features then encoding in vector sent for output to a classifier.
2)Fine-tuned to pre-made architecture
3)comparison of the proposed schemes with each other using accuracy, time, and AUC.
Reduction in false positives.
Improvements in false negatives.
Faster, accurate, and precise results
Machine learning models with high accuracy.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| graphic card for model training | Equipment | 1 | 70000 | 70000 |
| Total in (Rs) | 70000 |
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