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Zheen Hospital Heart Attack Prediction Database
Patient Health Records & Digital Health
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About
Predicting the likelihood of a heart attack using clinical observations facilitates early diagnosis and potential life-saving interventions. This collection of medical records provides a focused look at various physiological and biochemical markers recorded from patients. By classifying outcomes into distinct categories—either a heart attack occurred or it did not—the information serves as a vital tool for understanding the relationship between common health metrics and acute cardiac events.
Columns
- Age: The numerical age of the patient, ranging from 14 to 103 years.
- Gender: The sex of the patient, where male is represented by 1 and female by 0.
- Heart rate: The number of heartbeats per minute recorded for the individual.
- Systolic blood pressure: The top number in a blood pressure reading, measuring the force of blood against artery walls during a heartbeat.
- Diastolic blood pressure: The bottom number in a blood pressure reading, measuring the force between heartbeats.
- Blood sugar: The level of glucose present in the patient's blood.
- CK-MB: A measurement of creatine kinase-myocardial band, an enzyme used as a marker for heart muscle damage.
- Troponin: A protein released during a heart attack, with higher levels indicating potential damage.
- Result: The diagnostic outcome, where 1 signifies a positive heart attack classification and 0 indicates a negative result.
Distribution
The data is delivered in a CSV file titled Medicaldataset.csv, with a total file size of 52.36 kB. It contains 1,319 valid records across 9 distinct columns. The information demonstrates high integrity, with 100% validity across all entries and no reported missing or mismatched data points. The resource is maintained as a static collection with no future updates expected.
Usage
This resource is ideal for training machine learning models to perform binary classification tasks in a healthcare setting. It can be used to benchmark the accuracy of different algorithms in predicting cardiac outcomes based on clinical markers. Researchers can also perform statistical analysis to determine which factors, such as blood pressure or enzyme levels, have the strongest correlation with heart attack results.
Coverage
Geographically, the scope of this information is limited to records collected at Zheen Hospital in Erbil, Iraq. Temporally, the observations were gathered over a five-month period between January 2019 and May 2019. The demographic range is broad, covering adult and elderly populations with a mean age of approximately 56 years.
License
CC BY-SA 4.0
Who Can Use It
Data scientists can utilise these metrics to develop predictive healthcare applications and practice handling clinical datasets. Medical researchers may find the enzyme and protein markers valuable for studying the biochemical signs of cardiac distress. Additionally, educators can use the structured format of the data to teach students about medical diagnostic modelling and the importance of feature normalisation in data science.
Dataset Name Suggestions
- Zheen Hospital Heart Attack Prediction Database
- Clinical Cardiac Markers and Diagnostic Outcomes (2019)
- Heart Attack Predictive Feature Set: Erbil Iraq
- Biochemical and Physiological Heart Health Registry
Attributes
Original Data Source: Zheen Hospital Heart Attack Prediction Database
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