I am actually looking for An Improved Machine Learning Technique for Early Detection of Breast Cancer
Dear James Ade
In the machine learning, none of the algorithms are best for a particular type of problem. You have to choose the algorithms based on the complexity of your problem and dataset you use. If it is an image dataset you can use the deep learning algorithms if it is tabular dataset you can use the machine learning algorithms.
You have to just follow the basic machine learning pipeline to calculate the result of algorithm on your dataset if it is not working use the another one. Do follow the following things in each step:
1. EDA
2. Feature Engineering
3. Feature Selection
4. Use the algorithms to calculate the results.
5. Do the hyperparameter tuning using the GridSerachCV, RandomSearchCV, Genetic Algorithms etc.
6. Again calculate the accuracy
If the accuracy satisfy your requirements then deploy this model otherwise choose the next algorithm and repeat the above steps.
Thank you.
Hope you find it useful.
More innovate ways are emerging, you can check these links.
Article Early Diagnosis of Breast Cancer
https://www.cancer.org/cancer/breast-cancer/screening-tests-and-early-detection.html
https://www.ncbi.nlm.nih.gov/books/NBK223396/
Article Breast Cancer Early Detection: A Phased Approach to Implementation
https://www.breastcancer.org/symptoms/testing/types/self_exam
In my opinion, the crucial issue is to have an accurate dataset in the first place, from which the model will learn from. As soon as you have it, now you can search for how you want to implement your models.
There are several techniques that perform image classification and segmentation. Therefore it depends on what are you looking to predict (e.g. are you looking to only predict the existence of cancer?
Or, are you looking to predict the exact location of cancer? if So, are you going to predict it as an image or as a volume?
Dear James Ade
Check these article,
Article Breast Cancer Segmentation From Thermal Images Based on Chao...
Chapter Breast Cancer Detection and Classification Using Thermograph...
The review paper summarized some AI techniques in this way
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6278839/
You can consider using metaheuristics in combination with machine learning classifiers
As the dataset you indicated contains mammographies (images), Deep Learning (DL) is the best choice. Google already proposed an intelligent system based on DL, which seems to have the best performance on mammographies. You can search.
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