Cardio vascular disease prediction
Cardiovascular disease occurs the most highly effective results on human life. Almost eight out of ten people face death in this deadly disease. Cardiovascular is the term which is used to describe the variety of heart disease, illness and events that make an impact on the heart. The prediction of h
Project Title
Cardio vascular disease prediction
Project Area of Specialization
Project Summary
| Cardiovascular disease occurs the most highly effective results on human life. Almost eight out of ten people face death in this deadly disease. Cardiovascular is the term which is used to describe the variety of heart disease, illness and events that make an impact on the heart. The prediction of heart disease is a very challenging research problem for the researchers. The main aim of this research is to make an effective and suitable method using datasets with techniques of data mining. There are millions of datasets available, but the effective and progressive usage of that data will be part of the future. One of the most important data mining objectives is the medical field. Applications of these techniques in this area of cardiovascular disease are very necessary. A mined and particularly discovered knowledge of data will be helpful for the doctors to diagnose the cardiovascular disease. In this research paper, we presented an analysis of the Heart disease prediction using data mining techniques. In the health concern business, data mining performs a significant task for predicting diseases. A numeral number of tests must be required from the patient for detecting disease. However, using the data mining technique can reduce the number of tests that are required. The preprocessed data set consists of thousands of rows, which have all the available eight fields from the database. Cardiovascular disease is the main common source of deaths, and Heart Disease's prediction is significant at an untimely phase. To shorten the number of deaths from heart diseases there has to be a quick and efficient detection technique. |
Cardiovascular disease occurs the most highly effective results on human life. Almost eight out of ten people face death in this deadly disease. Cardiovascular is the term which is used to describe the variety of heart disease, illness and events that make an impact on the heart. The prediction of heart disease is a very challenging research problem for the researchers. The main aim of this research is to make an effective and suitable method using datasets with techniques of data mining. There are millions of datasets available, but the effective and progressive usage of that data will be part of the future. One of the most important data mining objectives is the medical field. Applications of these techniques in this area of cardiovascular disease are very necessary. A mined and particularly discovered knowledge of data will be helpful for the doctors to diagnose the cardiovascular disease. In this research paper, we presented an analysis of the Heart disease prediction using data mining techniques. In the health concern business, data mining performs a significant task for predicting diseases. A numeral number of tests must be required from the patient for detecting disease. However, using the data mining technique can reduce the number of tests that are required. The preprocessed data set consists of thousands of rows, which have all the available eight fields from the database. Cardiovascular disease is the main common source of deaths, and Heart Disease's prediction is significant at an untimely phase. To shorten the number of deaths from heart diseases there has to be a quick and efficient detection technique.
Project Objectives
| Cardiovascular disease occurs the most highly effective results on human life. Almost eight out of ten people face death in this deadly disease. Cardiovascular is the term which is used to describe the variety of heart disease, illness and events that make an impact on the heart. The prediction of heart disease is a very challenging research problem for the researchers. The main aim of this research is to make an effective and suitable method using datasets with techniques of data mining. There are millions of datasets available, but the effective and progressive usage of that data will be part of the future. One of the most important data mining objectives is the medical field. Applications of these techniques in this area of cardiovascular disease are very necessary. A mined and particularly discovered knowledge of data will be helpful for the doctors to diagnose the cardiovascular disease. In this research paper, we presented an analysis of the Heart disease prediction using data mining techniques. In the health concern business, data mining performs a significant task for predicting diseases. A numeral number of tests must be required from the patient for detecting disease. However, using the data mining technique can reduce the number of tests that are required. The preprocessed data set consists of thousands of rows, which have all the available eight fields from the database. Cardiovascular disease is the main common source of deaths, and Heart Disease's prediction is significant at an untimely phase. To shorten the number of deaths from heart diseases there has to be a quick and efficient detection technique. |
Cardiovascular disease occurs the most highly effective results on human life. Almost eight out of ten people face death in this deadly disease. Cardiovascular is the term which is used to describe the variety of heart disease, illness and events that make an impact on the heart. The prediction of heart disease is a very challenging research problem for the researchers. The main aim of this research is to make an effective and suitable method using datasets with techniques of data mining. There are millions of datasets available, but the effective and progressive usage of that data will be part of the future. One of the most important data mining objectives is the medical field. Applications of these techniques in this area of cardiovascular disease are very necessary. A mined and particularly discovered knowledge of data will be helpful for the doctors to diagnose the cardiovascular disease. In this research paper, we presented an analysis of the Heart disease prediction using data mining techniques. In the health concern business, data mining performs a significant task for predicting diseases. A numeral number of tests must be required from the patient for detecting disease. However, using the data mining technique can reduce the number of tests that are required. The preprocessed data set consists of thousands of rows, which have all the available eight fields from the database. Cardiovascular disease is the main common source of deaths, and Heart Disease's prediction is significant at an untimely phase. To shorten the number of deaths from heart diseases there has to be a quick and efficient detection technique.
Project Implementation Method
- Collection of Knowledge of Domain
- Collection of Research Papers
- Introduction of Work (Written)
- Consult with Cardiologist
- Collection of Datasets
- Problem Statement (Disease, Data Mining)
- Literature Review
- Initialization of Methodology
Complete Report for FYP 1
Benefits of the Project
we aim to predict accuracy, whether the individual is at risk of a heart disease. This prediction will be done by applying Data mining algorithms/Techniques on training data. Once the person enters the information that is requested, the algorithm is applied and the result is generated. Obviously, the accuracy is expected to decrease when the medical data itself are incomplete
Technical Details of Final Deliverable
- Creation of Framework
- Data Processing
- Training of Models
- Implementation of Models
- Result (Accuracy)
- Comparative Analysis
- Conclusion
- Complete Report of Project With Analysis
Final Deliverable of the Project
Core Industry
Other Industries
Core Technology
Other Technologies
Sustainable Development Goals
Required Resources
| Cardiovascular disease occurs the most highly effective results on human life. Almost eight out of ten people face death in this deadly disease. Cardiovascular is the term which is used to describe the variety of heart disease, illness and events that make an impact on the heart. The prediction of heart disease is a very challenging research problem for the researchers. The main aim of this research is to make an effective and suitable method using datasets with techniques of data mining. There are millions of datasets available, but the effective and progressive usage of that data will be part of the future. One of the most important data mining objectives is the medical field. Applications of these techniques in this area of cardiovascular disease are very necessary. A mined and particularly discovered knowledge of data will be helpful for the doctors to diagnose the cardiovascular disease. In this research paper, we presented an analysis of the Heart disease prediction using data mining techniques. In the health concern business, data mining performs a significant task for predicting diseases. A numeral number of tests must be required from the patient for detecting disease. However, using the data mining technique can reduce the number of tests that are required. The preprocessed data set consists of thousands of rows, which have all the available eight fields from the database. Cardiovascular disease is the main common source of deaths, and Heart Disease's prediction is significant at an untimely phase. To shorten the number of deaths from heart diseases there has to be a quick and efficient detection technique. |
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