Prediction of the Global Stomach Cancer Mortality in 2024

Jinyang Luo

2023

Abstract

Despite a huge decrease in stomach cancer incidence and mortality over recent decades, it remains a significant global health challenge. Stomach cancer was the fifth most typical factor contributing to cancer-related fatalities globally in 2020. This study employs linear regression to forecast stomach cancer mortality rates for 2024, considering historical data and various socio-economic and healthcare factors. The findings suggest a favorable trend in stomach cancer mortality for most countries, with notable declines in the number of deaths, and age-standardized death rate. At the same time, the percentage of stomach cancer deaths out of total deaths is increasing. The research highlights the impact of advancements in technology and medical treatments on reducing mortality rates and underscores the importance of early detection and prevention efforts. While predicting results. The COVID-19 pandemic’s limitations and potential impacts on cancer detection and therapy are acknowledged in the report.

Paper Citation

in Harvard Style

Luo J. (2023). Prediction of the Global Stomach Cancer Mortality in 2024. In Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-705-4, SciTePress, pages 154-158. DOI: 10.5220/0012809500003885

in Bibtex Style

@conference{daml23,
author={Jinyang Luo},
title={Prediction of the Global Stomach Cancer Mortality in 2024},
booktitle={Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2023},
pages={154-158},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012809500003885},
isbn={978-989-758-705-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - Prediction of the Global Stomach Cancer Mortality in 2024
SN - 978-989-758-705-4
AU - Luo J.
PY - 2023
SP - 154
EP - 158
DO - 10.5220/0012809500003885
PB - SciTePress