Forthcoming Articles

International Journal of Computers in Healthcare

International Journal of Computers in Healthcare (IJCIH)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Computers in Healthcare (One paper in press)

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  • Chest pain type prediction using parametric features of heart disease   Order a copy of this article
    by Bijayalaxmi Panda, Pratyush Mishra, Chhabi Rani Panigrahi, Bibudhendu Pati 
    Abstract: Heart disease often causes chest pain due to reduced blood flow to the heart muscle, known as angina. It results from narrowed or blocked coronary arteries. The pain can be sharp, squeezing, or a feeling of pressure. Immediate medical attention is crucial to prevent serious complications like heart attack. In this research, we analysed four types of chest pain based on features of heart disease. We took two heart disease datasets from Kaggle and were combined to form 1,295 instances. The dataset consists of several attributes for heart disease detection and is one of the attribute is chest pain. Several applications of exploratory data analysis (EDA) were performed to analyse the variables affecting heart disease. We have used different types of measures such as interaction, correlation, time series analysis for several attributes affecting heart disease. After performing feature selection some of the attributes taken as inputs that detect the type of chest pain which may or may not create the risk of heart disease.
    Keywords: chest pain; exploratory data analysis; EDA; extremely randomised trees classifier; light gradient boosting methods; extreme gradient boosting classifier.
    DOI: 10.1504/IJCIH.2025.10073327
     

 

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