Comparing the current short-term cancer incidence prediction models in Brazil with state-of-the-art time-series models.

ABSTRACT: The World Health Organization has highlighted that cancer was the second-highest cause of death in 2019. This research aims to present the current forecasting techniques found in the literature, applied to predict time-series cancer incidence and then, compare these results with the current methodology adopted by the Instituto Nacional do Câncer (INCA) in Brazil. A set of univariate time-series approaches is proposed to aid decision-makers in monitoring and organizing cancer prevention and control actions. Additionally, this can guide oncological research towards more accurate estimates that align with the expected demand. Forecasting techniques were applied to real data from seven types of cancer in a Brazilian district. Each method was evaluated by comparing its fit with real data using

SUBMITTER: Bouzon Nagem Assad D 

PROVIDER: S-EPMC10894878 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature