Wireless Holter Monitor Cardiac Patients Dataset

Citation Author(s):
Azlaan
Ranjha
National University of Sciences and Technology College of EME
Submitted by:
Azlaan Ranjha
Last updated:
Fri, 12/08/2023 - 21:48
DOI:
10.21227/46at-8d94
Data Format:
License:
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Abstract 

The dataset encompasses an extensive collection of patient information, delving into their comprehensive medical background, encompassing a myriad of features that encapsulate not only the physical but also the mental and emotional states. Furthermore, the dataset is enriched with invaluable ECG data derived from the patients. Moreover, our dataset boasts additional features meticulously extracted from the ECG records, thereby enhancing the potential for our machine learning model to undergo more effective training with our rich and diverse data. It is noteworthy that the initial column in the dataset serves a binary function, distinctly indicating whether the patient has been diagnosed with cardiac diseases or not. This crucial attribute not only serves as a fundamental element of our dataset structure but also plays a pivotal role in guiding the predictive capabilities of the machine learning model.

Instructions: 

The dataset is conveniently structured as a .csv file, ensuring seamless importation into various analytical tools and platforms. While a significant portion of the data preprocessing and feature extraction has already been meticulously undertaken, offering users a solid foundation to work with, it's important to highlight the flexibility inherent in the dataset. Users have the autonomy to effortlessly tailor and customize the dataset to align with their specific requirements and research objectives. This adaptability not only simplifies the integration of the dataset into diverse analytical workflows but also empowers users to fine-tune the dataset to their unique needs, fostering a dynamic and user-friendly environment for exploratory analysis and model development.