Diabetes Prediction Using Machine Learning Techniques

Project Title

Diabetes Prediction Using Machine Learning Techniques

Project Area of Specialization Artificial IntelligenceProject Summary

We have to describe a machine learning approach for  predicting diabetes. In the past the  diabetes was very dangerous diseases that cause the premature death. The studies show that its possible for some people to keep the sugar level in limits. Through diet changes and weight lose you may be able to reach and hold normal blood sugar levels without medication. Existing system are expensive and they need a blood sample. Inorder to overcome this limitation we will use machine learning to predicts diabetes disease with out taking the blood samples. In this project we will predict the diabetes by using SVM machine learning algorithm and find out weather a person has diabetes or not.

We have to describe a machine learning approach for  predicting diabetes. In the past the  diabetes was very dangerous diseases that cause the premature death. The studies show that its possible for some people to keep the sugar level in limits. Through diet changes and weight lose you may be able to reach and hold normal blood sugar levels without medication. Existing system are expensive and they need a blood sample. Inorder to overcome this limitation we will use machine learning to predicts diabetes disease with out taking the blood samples. In this project we will predict the diabetes by using SVM machine learning algorithm and find out weather a person has diabetes or not.

Project Objectives

Machine learning is an excellent technology for predicting data in the medical field. Machine learning automatically predicts large amount of data in a very short time with minimum interaction with patient. Which saves a lot of time and money. We propose a diabetes prediction system for better diagnosis without any medical persons (doctor) or machine. The goal of this project is to make use of  Machine Learning Algorithms, to predict whether a person has diabetes. Prediction of diabetes at an early stage can lead to initiate treatment and can prevent a lot of serious other health problems.

Machine learning is an excellent technology for predicting data in the medical field. Machine learning automatically predicts large amount of data in a very short time with minimum interaction with patient. Which saves a lot of time and money.

We propose a diabetes prediction system for better diagnosis without any medical persons (doctor) or machine. The goal of this project is to make use of  Machine Learning Algorithms, to predict whether a person has diabetes. Prediction of diabetes at an early stage can lead to initiate treatment and can prevent a lot of serious other health problems.

Project Implementation Method

The following step are used as an implementation method. The first step in the Machine Learning process is preparing the training data. We have to collect our dataset from Kaggle The training data we are going to use for this problem is the Pima Indian Diabetes database. The Algorithm we have to use in this project is Support vector machine (SVM) It is a supervised learning Algorithm in supervised learning model we feed the data into a machine learning model and the model learns from data with its respective labels. The Model then needs to be trained with the blood glucose level and insulin level and diabetes level to predict whether a person has diabetes or not. The programming language to be used in this project is python The environment to be used in this project is Google Collab and jupyter notebook.

The following step are used as an implementation method.

1. The first step in the Machine Learning process is preparing the training data. We have to collect our dataset from Kaggle
2. The training data we are going to use for this problem is the Pima Indian Diabetes database.
3. The Algorithm we have to use in this project is Support vector machine (SVM)
4. It is a supervised learning Algorithm in supervised learning model we feed the data into a machine learning model and the model learns from data with its respective labels.
5. The Model then needs to be trained with the blood glucose level and insulin level and diabetes level to predict whether a person has diabetes or not.
6. The programming language to be used in this project is python
7. The environment to be used in this project is Google Collab and jupyter notebook.

Benefits of the Project

This project is based on machine learning and it will make the prediction of diabetes at early stages to save the person from getting diabetes. diabetes prediction system will work without any medical persons or machine. The WHO (World Health Organization) reported that around 1.6 million people die due to diabetes every year. The efficient control of diabetes is possible if it can be detected early. So our diabetes prediction system will efficiently detect the diabetes of person at early stages, which will also save time and money.

Technical Details of Final Deliverable

The final deliverable of this project is make use of machine learning technology for building a diabetes prediction system. The Machine learning is an excellent technology for predicting data in the medical field. We have to use this technology for building a diabetes prediction system to predict whether a person has diabetes for better diagnosis without consulting a doctor.

Final Deliverable of the Project Software SystemCore Industry ITOther Industries Medical Core Technology Artificial Intelligence(AI)Other Technologies Artificial Intelligence(AI)Sustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Machine learning is an excellent technology for predicting data in the medical field. Machine learning automatically predicts large amount of data in a very short time with minimum interaction with patient. Which saves a lot of time and money. We propose a diabetes prediction system for better diagnosis without any medical persons (doctor) or machine. The goal of this project is to make use of  Machine Learning Algorithms, to predict whether a person has diabetes. Prediction of diabetes at an early stage can lead to initiate treatment and can prevent a lot of serious other health problems.