Work

Data preparation method for machine learning-based breast cancer risk prediction: A Cuban case study

Year: 2025

Type: article

Abstract: This article presents a dataset of breast cancer risk factors collected from 1697 Cuban women between 2001 and 2018, as a tool to design and support the development and validation of predictive models in public health for breast cancer risk. A reproducible methodology for quality control and variable enrichment was implemented to ensure data integrity and compatibility with machine learning techniques. • Reproducible preprocessing methodology to ensure data quality and traceability. • Open breast cancer risk factor dataset for epidemiological studies and risk assessment using machine learning. • Consistent prediction model performance across multiple metrics after data preprocessing.

Source: MethodsX

DOI: 10.1016/j.mex.2025.103688

Authors: Jose Manuel Valencia-Moreno, Everardo Gutierrez-Lopez, Jose Angel Gonzalez-Fraga, Rodolfo Alan Martinez Rodriguez, Olivia Denisse Victoria Mejia, Alma Alejandra Soberano Serrano

Institution: Universidad Autónoma de Baja California

Language: English

Topic: Artificial Intelligence in Healthcare

Subfield: Health Information Management

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,260