Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/3986
Title: | Identification of Cardiovascular Mortality Risk in Patients with Respiratory Disease |
Authors: | Reddy, Banda Sai Jashwanth Are, Ramakrishna Prasad Puneet, . Babu, Anju R |
Keywords: | Artificial neural networks Machine learning Mortality |
Issue Date: | Feb-2023 |
Citation: | Indian Conference on MedTech Innovations (ICMI), IIT Jodhpur, India, 24-26 February 2023 |
Abstract: | Circulatory and respiratory diseases are the leading cause of death. Recent studies suggest that respiratory diseases can increase the risk of cardiovascular disease, yet the reason is unknown. In this study, an artificial neural network model is built to predict the possibility of death due to cardiovascular disease with given respiratory conditions. Data shows that cardiovascular disease was an underlying cause for approximately 16.8 percent of the patients suffering from respiratory diseases. Chronic lower respiratory disease has the highest number of deaths, with 72,125 cases. Further studies are needed to find the exact symptoms causing death due to an underlying cause of cardiovascular diseases with respiratory diseases as one of its multiple conditions |
Description: | Copyright belongs to proceeding publisher |
URI: | http://hdl.handle.net/2080/3986 |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2023_ICMI_BSJReddy_Identification.pdf | 296.62 kB | Adobe PDF | View/Open |
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