A Method for Predicting Cardiovascular Disorder using Machine Learning Techniques
Drastic increase of cardiovascular disease has led to a lot of adult's death. As per "News 18" very year, 12 million young people in India die from heart disease. In most of these cases people experience cardiac arrest, some of which are normal. First, families of patients are vulnera...
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| Vydané v: | 2024 International Conference on Recent Advances in Science and Engineering Technology (ICRASET) s. 1 - 7 |
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21.11.2024
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| Abstract | Drastic increase of cardiovascular disease has led to a lot of adult's death. As per "News 18" very year, 12 million young people in India die from heart disease. In most of these cases people experience cardiac arrest, some of which are normal. First, families of patients are vulnerable because it takes only a few minutes for a person to die of a heart attack, and it is difficult to get medical help in time. Second, most victims are under the age of 45. According to Dr. Maninder Sandhu, cardiologist and cardiologist at Artemis Hospital Gurgaon, 30 percent of people who suffer from heart disease are under the age of 45. This paper proposes a method that maybe used by laboratory technicians, doctors and users to understand whether there are any chances of having cardiovascular disease or not. The proposed system takes live data of patients and their lifestyle attributes these data are processed by the trained model to produce the output. In this model we haveused random forest classifier, linear regression, \mathbf{k}-neighbors classifier & x gradient boost classifier. This model has attained maximum accuracy and least type one error in "X- Gradient Boost". We have concentrated more on type one error. The developed system shows whether the patient has any chances of cardiovascular disease or not. |
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| AbstractList | Drastic increase of cardiovascular disease has led to a lot of adult's death. As per "News 18" very year, 12 million young people in India die from heart disease. In most of these cases people experience cardiac arrest, some of which are normal. First, families of patients are vulnerable because it takes only a few minutes for a person to die of a heart attack, and it is difficult to get medical help in time. Second, most victims are under the age of 45. According to Dr. Maninder Sandhu, cardiologist and cardiologist at Artemis Hospital Gurgaon, 30 percent of people who suffer from heart disease are under the age of 45. This paper proposes a method that maybe used by laboratory technicians, doctors and users to understand whether there are any chances of having cardiovascular disease or not. The proposed system takes live data of patients and their lifestyle attributes these data are processed by the trained model to produce the output. In this model we haveused random forest classifier, linear regression, \mathbf{k}-neighbors classifier & x gradient boost classifier. This model has attained maximum accuracy and least type one error in "X- Gradient Boost". We have concentrated more on type one error. The developed system shows whether the patient has any chances of cardiovascular disease or not. |
| Author | Shivashankara, S Pavithra, D R Soumyasri, S M Prasanna Kumar, G Nagashree, S Hegde, Ramakrishna |
| Author_xml | – sequence: 1 givenname: Ramakrishna surname: Hegde fullname: Hegde, Ramakrishna email: ramhegde111@gmail.com organization: Affiliated to Visvesvaraya Technological University,Computer Science and Engg. Vidyavardaka College of Engineering,Belagavi,India – sequence: 2 givenname: D R surname: Pavithra fullname: Pavithra, D R email: pavithra@sjce.ac.in organization: JSS Science and Technology University,Electronics & Communication Engg., Sri Jayachamarajendra College of Engineering,Mysuru,India – sequence: 3 givenname: S surname: Shivashankara fullname: Shivashankara, S email: shivashankar.research@gmail.com organization: KR Pete Krishna Government Engineering College,Computer Science and Engg.,Krishnarajapet,India – sequence: 4 givenname: G surname: Prasanna Kumar fullname: Prasanna Kumar, G email: g3p3k@gmail.com organization: The National Institute of Engineering,Information Science & Engg.,Mysore,India – sequence: 5 givenname: S M surname: Soumyasri fullname: Soumyasri, S M email: drsoumyasrism@gmail.com organization: Affiliated to Visvesvaraya Technological University,Dept. of Computer Applications Vidya Vikas Inst. of Engg. and Tech,Belagavi,India – sequence: 6 givenname: S surname: Nagashree fullname: Nagashree, S email: nagashree.vviet@gmail.com organization: Vidya Vikas Institute of Engineering and Technology,Electronics and communication Engg,Mysuru,India |
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| Snippet | Drastic increase of cardiovascular disease has led to a lot of adult's death. As per "News 18" very year, 12 million young people in India die from heart... |
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| SubjectTerms | Accuracy Cardiac arrest Cardiovascular Disease Classification algorithms Feature extraction Heart K Nearest Neighbour algorithm Linear regression Machine Learning Nearest neighbor methods Prediction algorithms Predictive models Random Forest Classifier Random forests |
| Title | A Method for Predicting Cardiovascular Disorder using Machine Learning Techniques |
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