Breast cancer prediction using machine learning

Breast cancer is the most common forms of cancer in women these days. It is generally prevalent in the women of the middle ages. But the early diagnosis of breast cancer can help in the early treatment of this cancer, which will increase the rate of survival. In breast cancer, a tumour gets formed in the breast region of the body. So, even breast cancer have different stages, which is determined by looking at how much the tumour has enlarged or spread. In case, you also want to determine the same, you can get in touch with cancer hospital in Noida.

Hence, the point is that you can take the correct diagnosis of breast cancer at the proper time is vital for the treatment. Otherwise, the tumour may enlarge and hence, the chances of death due to cancer increase. Because of its unique advantages – Breast Cancer datasets, machine learning is widely recognized as the methodology of choice in Breast Cancer pattern classification and forecast modeling.

Risk Factors for Breast Cancer

However, in most of the cases of breast cancer, the reason is not specific. But there are several reasons which can increase the risk factor of Breast Cancer:

Age -The chances of a woman getting breast cancer increases with her age. Almost 80% of the cases of breast cancer were reported in women of 50 years of age.

Personal history of breast cancer –Women having cancer in one breast have more chance of getting cancer in the other breast, as well.

Family history of breast cancer – Women whose mother, sister or any other women relative has breast cancer has an increased chance of getting breast cancer.

Genetic Disorders- Women having certain genetic disorders are more likely to get breast cancer.

Childbearing and menstrual history- Older women are while giving birth to her first child; more is the chance of getting breast cancer. Also, women having the following disorders are likely to get breast cancer:

  1. Women who menstruate for the first time at an early age than others.
  2. Women who go through menopause late than other women.
  3. Women who’ve never got pregnant or never had any children.

 

How Machine Learning can help

With the advancement in technology in medical fields. Daily new methods of treatments and diagnosis are coming. Different Methods of diagnosis of breast cancer through the machine programs are happening in the medical areas. It is a new technology and goes through some phases for the diagnosis of breast cancer. Various stages in diagnosing breast cancer through machine learnings are:

Step – 0 (Data preparation)

To create the dataset used for the diagnosis of breast cancer, doctors used fluid samples, taken from patients with solid breast masses. After these, the data samples are fed up in the computers. The data samples might include the texture and perimeter of the breast. This phase includes all the efforts for data collection and input in the computer systems.

Phase – 1 (Data Exploration)

This phase deals with the understanding with the data and comparing the affected person data with unaffected person’s data. Data in this phase is represented in the form of charts, rows and columns for better understanding of the data.

Phase – 2 (Categorical Data)

Categorical data are variables that contain label values than numeric values. It is often limited and is fixed to a set. For example, users are typically described by age, gender, country etc.

This helps in understanding the reports of breast cancer age-wise, gender-wise and geography wise.

Phase – 3 (Feature Scaling)

The dataset collected generally contains data types which are highly varying in magnitudes, units and range. But since, machines can only understand the binary language or the language of 0 and 1; then this phase is the phase of conversion of all kind of data in computer understandable forms. This can be achieved by scaling. This means that we are transforming your data so that the computer can understand it.

Phase – 4 (Model selection)

This is the best phase in applying machine learning to any set of data. This phase is known as Algorithm selection, and it helps in predicting the best results.

Usually, Data scientists use various kinds of machine learning algorithms

For data sets. In the higher levels of data, data are divided into types: supervised learning and unsupervised learning.

After the data collected passes through these phases, and the conditions of the breast cancer are fed, if the data matches with data with the affected person data, then there can be the substantial probability of having breast cancer.

After these, several other medical tests are done to confirm the situation of breast cancer and the stage in which the tumour is. Thus this is the complete functioning of the machine programs for diagnosis of machine learning.

Conclusion

With the advancement of technology in the medical fields, we are looking at the new methods of diagnosing, treatments and surgeries. In these groups of ways, now a new type called machine programming also have been included which uses machine algorithms to diagnose breast cancer using the data and samples of breast cancer. This can be seen as a revolution in the medical field. This will also help in reducing the cost of diagnosis of breast cancer, and most importantly, it will help in early diagnosis, which will help in early treatments and hence will grow the chances of survival.

Get in touch with Dr. Vikas Goswami to treat your cancer.

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