Heart Disease Prediction USING ML and Pandas
DOI:
https://doi.org/10.15680/IJCTECE.2026.0902009Keywords:
Heart disease prediction, machine learning, Healthcare Analytics, Classification Algorithms, Early Detection, Medical DataAnalysis, Risk Management, Predictive ModelingAbstract
Heart disease is one of the learning causes of death around the world . many people do not notice symptoms in the early stages , which makes early detection very important this project focuses on predicting heart disease using machine learning techniques . the system collects important medical details such age, blood presser , cholesterol level, heart rate, and other health factors to analyses person’s condition.
Different machine learning algorithms are used to study past patient data and identify patterns related to heart disease. based on these patterns , the model checks the data and tells us if a person may have a heart risk . the main aim to this project is to help doctors and patients detect heart problems at an early stage so that proper treatment and preventive steps can be taken.
By using technology and data analysis , this model provides a faster , cost -effective , and reliable method foe heart disease prediction . this system can support medical professional in making better decisions and improving patient care
The model trained using medical data to improve prediction accuracy. If provides result in a short time, making the process efficient and user friendly. The approach can help in spreading awareness and encourages regular health checkups.
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