Exploring Non-Communicable Disease Risk Factors on Cancer Rates in Central Java Using Random Forest and SHAP

Non-communicable diseases (NCDs), including cancer, account for over 75% of global deaths, with cancer being the second leading cause.In Indonesia, cancer ranks third, and Central Java has a high prevalence of 1.7 per 1,000 population in 2023.This study analyzed cancer incidence in Central Java using a Random Forest model combined with SHapley Additive exPlanations (SHAP) to assess local feature importance.Key risk factors identified include the presence of sugar-sweetened beverage outlets, which affect 28.6% of districts, air pollution from SO and NO, which impacts 22.9% and 11.4% of districts, respectively, and the presence of slum areas, which is associated with higher cancer risks in 8.6% of districts.These findings offer insights into targeted public health strategies aimed at reducing cancer incidence and improving community health.

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Publication Details

Journal
Proceedings of International Conference on Artificial Life and Robotics
Published
2025-02-13
DOI
https://doi.org/10.5954/icarob.2025.os26-10
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Exploring Non-Communicable Disease Risk Factors on Cancer Rates in Central Java Using Random Forest and SHAP

Naser Ramadani, Andi Prademon Yunus
Proceedings of International Conference on Artificial Life and Robotics
Artificial Intelligence in Healthcare
article

Exploring Non-Communicable Disease Risk Factors on Cancer Rates in Central Java Using Random Forest and SHAP

Naser Ramadani, Andi Prademon Yunus
article en

Abstract

Non-communicable diseases (NCDs), including cancer, account for over 75% of global deaths, with cancer being the second leading cause.In Indonesia, cancer ranks third, and Central Java has a high prevalence of 1.7 per 1,000 population in 2023.This study analyzed cancer incidence in Central Java using a Random Forest model combined with SHapley Additive exPlanations (SHAP) to assess local feature importance.Key risk factors identified include the presence of sugar-sweetened beverage outlets, which affect 28.6% of districts, air pollution from SO and NO, which impacts 22.9% and 11.4% of districts, respectively, and the presence of slum areas, which is associated with higher cancer risks in 8.6% of districts.These findings offer insights into targeted public health strategies aimed at reducing cancer incidence and improving community health.

Proceedings of International Conference on Artificial Life and RoboticsVol. 30
Telkom University (ID)
Openalex Percentile: Top 75%
Artificial Intelligence in Healthcare
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