Investigating Patterns and Associations of Different Cancer Types in Peru: A Data-driven Approach

This study examines whether the incidence of the most common cancers in Peruvian society is associated with access to health services and socioeconomic individual characteristics. The aim was to investigate the relationship between common cancers, individual patient characteristics, health centre locations and the Human Development Index of Peruvian society. Data were obtained from the Peruvian Open Data Platform and provided by the Fondo Intangible Solidario de Salud (FISSAL, by its Spanish acronym). We analysed 513,530 records of oncological care and performed chi-squared tests to examine the association between different cancer types and other characteristics, comparing observed data with expected proportions of different cancer services. Through a comprehensive analysis of these variables, we aim to uncover patterns and associations that can inform health policy and resource allocation, and ultimately contribute to better cancer prevention and treatment strategies in Peru. This study highlights the critical interplay of data science to provide insights and inform public health strategies regarding structural inequalities that have serious health consequences in Peruvian society.

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Published
2024-11-06
DOI
https://doi.org/10.1109/intercon63140.2024.10833471
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

Investigating Patterns and Associations of Different Cancer Types in Peru: A Data-driven Approach

Rosmery Ramos‐Sandoval, Nicolás Ismael Alayo Arias, Arelly Fernanda Vega Peche
Artificial Intelligence in Healthcare
article

Investigating Patterns and Associations of Different Cancer Types in Peru: A Data-driven Approach

Rosmery Ramos‐Sandoval, Nicolás Ismael Alayo Arias, Arelly Fernanda Vega Peche
article en

Abstract

This study examines whether the incidence of the most common cancers in Peruvian society is associated with access to health services and socioeconomic individual characteristics. The aim was to investigate the relationship between common cancers, individual patient characteristics, health centre locations and the Human Development Index of Peruvian society. Data were obtained from the Peruvian Open Data Platform and provided by the Fondo Intangible Solidario de Salud (FISSAL, by its Spanish acronym). We analysed 513,530 records of oncological care and performed chi-squared tests to examine the association between different cancer types and other characteristics, comparing observed data with expected proportions of different cancer services. Through a comprehensive analysis of these variables, we aim to uncover patterns and associations that can inform health policy and resource allocation, and ultimately contribute to better cancer prevention and treatment strategies in Peru. This study highlights the critical interplay of data science to provide insights and inform public health strategies regarding structural inequalities that have serious health consequences in Peruvian society.

Universidad Tecnológica del Perú (PE)
Openalex Percentile: Top 64%
Artificial Intelligence in Healthcare
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Investigating Patterns and Associations of Different Cancer Types in Peru: A Data-driven Approach — Rosmery Ramos‐Sandoval, Nicolás Ismael Alayo Arias, et al. · (2024) | TGRS Research Map | TGRS