ISSN (Online): 2321 - 7782
ISSN (Print): 2347 - 1778

VOLUME 12, ISSUE 7, July - 2024

Innovative Modeling of Stroke Risk Using Healthcare Data

Author(s) :   Akshita Rahangdale

Abstract : This dataset comprises medical and demographic information about individuals, with an emphasis on characteristics that may be related with stroke. The dataset contains 12 attributes: a unique patient ID, gender, age, hypertension status, heart disease status, marital status, and kind of job, type of dwelling, average glucose level, body mass index (BMI), smoking status, and stroke incidence. The main features are as follows:

Demographic characteristics include gender, age, marital status, place of residence, and kind of employment.

Medical attributes include hypertension, heart disease, average glucose level, BMI, and smoking status. Stroke occurrence (a binary outcome showing if the patient experienced a stroke).

Keywords: Stroke Epidemiology, Public Health, Medical Data, Chronic Disease Management.

DOI : 10.61161/ijarcsms.v12i7.33

Pages : 270-276



How to Cite this aricle?
Rahangdale, A. (2024). Innovative Modeling of Stroke Risk Using Healthcare Data. INTERNATIONAL JOURNAL OF ADVANCE RESEARCH IN COMPUTER SCIENCE AND MANAGEMENT STUDIES, 12(7), 270–276. https://doi.org/10.61161/ijarcsms.v12i7.33

*Authors are invited to submit papers through E-mail at editor.ijarcsms@gmail.com