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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      1 Jan 2024, Volume 39 Issue 1   
    Article

    ANALYSING PREDICTORS OF HEALTHCARE RESOURCE CONSUMPTION AMONG CANCER PATIENTS: A COMPREHENSIVE REGRESSION MODELING STUDY
    Dr. Mrinal Deka
    Journal of Data Acquisition and Processing, 2024, 39 (1): 1237-1247 . 

    Abstract

    In this particular study, various risk factors such as socio-economic status, demographics, and clinical factors have been successfully identified for lung and oral cancer. The research indicates that patient age, tumour size, node size and blood sugar levels adversely affect cancer patient survival times, with increased values corresponding to decreased survival times. Furthermore, the study addresses the critical issue of selecting an appropriate survival model and concludes that the Weibull survival model is the most suitable option. This conclusion is drawn based on the lower Akaike Information Criterion (AIC) values obtained compared to other models across all cancer types. The findings suggest that survival times estimated from this model are reliable, facilitating predictions of cancer patient survival times based on available data.

    Keyword

    Lung Cancer, Oral Cancer, Risk factors, Parametric survival model, Bayesian Model


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ISSN 1004-9037

         

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