A Comparative Machine Learning Framework for Cardiovascular Disease Classification
Cardiovascular disease is one of the leading cause of death in Pakistan and around the globe. This emerging trend in Pakistan is uniformly rising due to the external factors that mainly affects the physical and mental health of people. Cardiovascular diseases (CVDs) are primary disorders of the bloo
2025-06-28 16:24:58 - Adil Khan
A Comparative Machine Learning Framework for Cardiovascular Disease Classification
Project Area of Specialization Artificial IntelligenceProject SummaryCardiovascular disease is one of the leading cause of death in Pakistan and around the globe. This emerging trend in Pakistan is uniformly rising due to the external factors that mainly affects the physical and mental health of people. Cardiovascular diseases (CVDs) are primary disorders of the blood vessels that mainly affects the heart. It is mainly linked to lipid deposits in the arteries and rapid rise or increase of the blood clots. It can lead towards destruction of the organ which mainly affects the coronary arteries which are the main supply for the nutrients and the oxygen levels. If these are disrupted it then will account for most of the organs damage. It is essentially important that people can identify and maintain their heart disease risk factors at an early onset so they may go for further treatment in future. To overcome this hurdle an in silico study is conducted using cardio informatics, machine learning algorithms and web design approaches to ease the people in identifying their heart rate condition. In our research we will obtain the cardiovascular disease data from kaggle and use machine learning algorithms such as using KNN, logistic and random forest that will allow the detection and classification prediction of cardiovascular condition. To perform programming, we will use Python for the back end programming and data analysis and the web application will be created using HTML. Our results will assist in prediction based on the BMI index the disease classification results that can be used in suggesting for further diagnosis. Emphasis on this research will benefit in adapting to classify pattern of using primary or minimal attributes from all available data in the dataset. This research will predict the possibility of cardiovascular disease based on the submitted data by user on web application which definitely expedite the research related to cardio informatics and serve the scientific community
Project ObjectivesIn this research our objectives are
- To perform comparission and classification through python programming using python libraries and KNN, random forest and logistic regression algorithms
- Design a web application that will ease the patients having concerned about their heart rate condion
PURPOSE:
Our purpose is to implement the heart disease classification first from using biological data available from kaggle and then design a website for the front end framework to be used by the people
OVERVIEW:
We will perform the classification through python programming which will be our back end development. We will design front end web development through HTML coding
DESCRIPTION
We will perform the python programming using python libraries like numpy, pandas, seaborn, matplotlib, sklearn. These libraries will help us load and work on our data frames. The use of these libraries will also help us in identifying meaning from the attributes of our data. Having the attribute factors such as physical health, mental health, sex, sleep time, smoking, alcoholic drinking, stroke will be the common factors we will be using in our research. For our programming the first thing we will do is remove outliers from our data and then use the classification algorithms which are KNN, logistic and random forest algorithm to perform the classification and prediction technique. For the logistic regression we will get the accuracy and precession scores for this algorithm and we will repeat the steps with the other algorithm from the data available and after that we will compare the random forest and KNN with the logistic regression using training dataset. Then we will design a website for the front end development of the webpage to be used by the users who wants to view their condition of the heart rate.
Benefits of the ProjectThis research is computationally efficient and will assist people in determining whether or not they have heart disease. This early onset prediction will allow users or even patients to consult with a doctor about their condition and seek further diagnostics. This would also save time for doctors and clinicians because they will know what caused their cardiac condition, allowing them to provide more effective treatment.
Technical Details of Final DeliverableOur user will have access to a web application that is open to the public. When we publish our article, we will also include a link to our online application. The user will first enter the BMI index number into the web application for our project. If the user does not know his or her BMI index, we will include a calculator in the program to assist them in figuring it. Users will be asked relevant questions like their age, sleeping hours, gender, and breathing conditions via our applications. On the basis of these characteristics, we'll employ machine learning algorithms in the backend to predict whether or not the user will develop cardiovascular disease. Our application will also show a graphical representation of the scores, allowing the user to quickly understand the results. We will also give users a plan if they are at risk of developing cardiovascular disease based on our prediction, and the program will advise them whether or not they should consult a doctor. For the user, a plan of what precautions they should take for this risk will be developed. If a user does not have cardiovascular disease, a plan will be created for them that will offer them with strategies to maintain a healthy heart.
Final Deliverable of the Project Software SystemCore Industry HealthOther Industries IT , Medical , Others Core Technology Artificial Intelligence(AI)Other Technologies Big DataSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 20000 | |||
| stationary | Miscellaneous | 50 | 40 | 2000 |
| poster | Miscellaneous | 2 | 1000 | 2000 |
| paneflex | Miscellaneous | 2 | 1000 | 2000 |
| printing (Black and colored) | Miscellaneous | 100 | 10 | 1000 |
| Thesis binding | Miscellaneous | 3 | 500 | 1500 |
| Bronchure | Miscellaneous | 4 | 200 | 800 |
| web hosting | Equipment | 1 | 10700 | 10700 |