Prediction of skin cancer invasiveness: A comparative study among the regions of Brazil

Marcus Augusto Padilha Mata, Plinio Sa Leitao-Junior
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引用次数: 0

Abstract

Context

Skin cancer is the most incident neoplasia in Brazil, and their invasiveness can be impacted by various factors, including geographical aspects. Identifying these factors is important for improving diagnosis and treatment.

Objective

The research focused on analyzing the impact of region on the invasiveness of skin cancer in Brazil, through the identification of regional predictive patterns.

Methods

An analysis and processing of data from the Hospital Cancer Registries (RHC) of Brazil's National Cancer Institute (INCA) were conducted, followed by the application of machine learning algorithms. The SHapley Additive exPlanations (SHAP) approach was employed to provide explanations for the developed artificial intelligence models.

Results

It was revealed that geography plays a significant role in predicting the invasiveness of skin cancer, reinforcing the need to consider regional specificities in future studies.

Conclusions

The study identified that regional characteristics of Brazil impacts the prediction of the invasiveness of skin cancer. Despite limitations, such as the issue of data imbalance, the findings are important for developing more effective policies in the fight against skin cancer in the Brazil.

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皮肤癌侵袭性预测:巴西各地区比较研究
背景皮肤癌是巴西发病率最高的肿瘤,其侵袭性会受到包括地理因素在内的各种因素的影响。方法对巴西国家癌症研究所(INCA)医院癌症登记处(RHC)的数据进行分析和处理,然后应用机器学习算法。结果表明,地理位置在预测皮肤癌的侵袭性方面起着重要作用,因此在今后的研究中更有必要考虑地区特性。结论该研究发现,巴西的地区特性对预测皮肤癌的侵袭性有影响。尽管存在数据不平衡等局限性,但研究结果对巴西制定更有效的皮肤癌防治政策非常重要。
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来源期刊
Intelligence-based medicine
Intelligence-based medicine Health Informatics
CiteScore
5.00
自引率
0.00%
发文量
0
审稿时长
187 days
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