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Heart Attack Prediction

This feature has been built with the intention of providing an early warning for Heart disease based on indicators collected by the wearable's sensor array. This feature seeks to provide users and their support network an alert to worrying decreases in cardiovascular health.

Data Analytics

To analyse this data, as well as to train machine learning classification models, a number of python libraries have been incorporated into the project:

Dataset 1

The dataset used in heart_attack_prediction.ipynb is the Heart Attack Risk Prediction Dataset synthesized by Sourav Banerjee with the assistance of ChatGPT1

NameDescriptionType
Patient IDNominal
AgeDiscrete: [years]
SexNominal: [Male, Female]
CholestrolTotal Cholestrol measuredDiscrete: [mg/dL]
Blood Pressure2 Values showing the pressure over the heart beating and the heart relaxingDiscrete: [Systotic/Diastolic (mm Hg)]
Heart RateDiscrete: [beats per minute]
DiabetesPresence of diabetes in the patientNominal: [1: Yes, 0: No]
Family HistoryNominal: [1: Yes, 0: No]
SmokingNominal: [1: Yes, 0: No]
ObesityNominal: [1: Yes, 0: No]
Alcohol ConsumptionNominal: [1: Yes, 0: No]
Hours of Exercise per WeekContinuous
DietOrdinal: [ Healthy, Average, Unhealth]
Previous Heart ProblemsNominal: [1: Yes, 0: No]
Medication UseNominal: [1: Yes, 0: No]
Stress LevelSelf-reported level of stressOrdinal: [1 ➡ 10]
Sedentry HoursPer DayContinuous
IncomeAnnual incomeContinuous
BMIBody-Mass Index: calculated by body-mass / height^2Continuous
TriglyceridesContinuous: [mg/dL]
Physical Activity Days Per WeekContinous
Sleep Hours Per DayContinous
Heart Attack RiskContinuous: [0➡1]

Dataset 2

Please cite the sources of this dataset. I tried my damndest but couldnt find it

The dataset used in the Heart_Disease_Prediction.ipynb notebook:

Footnotes

  1. https://www.kaggle.com/datasets/iamsouravbanerjee/heart-attack-prediction-dataset/data