ArticleSao Paulo medical journal = Revista paulista de medicina2025
Comparative analysis prediction of prostate and testicular cancer mortality using machine learning: accuracy study.
Article in Sao Paulo medical journal = Revista paulista de medicina, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe mortality rates of prostate and testicular cancer are higher mortality in the northeast region.
objectiveWe aimed to compare the efficacy of machine learning libraries in predicting testicular and prostate cancer mortality. DESIGN AND
settingA comparative analysis of the pyMannKendall and Prophet machine-learning algorithms was conducted to develop predictive models using data from DATASUS (TabNet) to Caicó (Brazil) and Rio Grande do Norte (Brazil).
methodsData on prostate and testicular cancer mortality in men from 2000 to 2019 were collected. The prediction accuracy of the Prophet algorithm was evaluated using the mean squared error (MSE), the root mean squared error and analyzed using the pyMannKendall, and Prophet libraries.
resultsThe research data were made publicly available on GitHub. The machine test confirmed the accuracy of the predictions, with the root MSE (RMSE) values closely matching the observed data for Caicó (RMSE = 2.46) and Rio Grande do Norte (RMSE = 22.85). The Prophet algorithm predicted an increase in prostate cancer mortality by 2030 in Caicó and Rio Grande do Norte. This prediction was corroborated by the pyMannKendall analysis, which indicated a 99% probability of a rising mortality trend in Caicó (P < 0.01; tau = 0.586; intercept = 2.59) and Rio Grande do Norte (P = 2.06; tau = 0.84, and intercept = 119.63). For testicular cancer, no significant mortality trend was identified by Prophet or pyMann-Kendall.
conclusionsLibraries are reliable tools for predicting mortality, providing support for strategic health planning, and implementing preventive measures to ensure men's health. Addressing the gender gap in DATASUS is essential.
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