RT info:eu-repo/semantics/dataPaper
T1 Mammography reporting dataset with BI-RADS system for natural language processing applications: addressing public data gaps in Spanish
A1 Vázquez Noguera, José Luis
A1 Torres Hurtado, Alejandro
A1 Gómez Adorno, Helena
A1 Mello Román, Julio César
A1 Fleitas Álvarez, Enrique Javier
A1 Espínola Schulze, Federico Fernando
A1 García Torres, Miguel
A1 Méndez Gaona, Carlos Domingo
A1 Gardel Sotomayor, Pedro Esteban
A1 Vázquez Noguera, Silvia
A1 Zaracho Amarilla, Norma Elizabeth
A1 Gamarra Esquivel, Oxades Wilfrido
A2 Universidad Americana/INCADE S.A.E
AB Applying Natural Language Processing (NLP) to clinical reports is important for automating the analysis and classification of clinical data, improving diagnostic accuracy, and enhancing healthcare workflows. This article presents a dataset derived from mammography reports written in Spanish collected across multiple medical units operated by the Oxades company in Paraguay. The dataset contains 4357 records and 15 variables, including the text of the complete report and also each of its sections separately (clinical observations, diagnostic conclusions, follow-up recommendations), and the BI-RADS (Breast Imaging Reporting and Data System) classification assigned to each one of the reports. Additionally, the dataset includes metadata such as report IDs, dates, and patient information such as age, patient reasons for the analysis, last menstruation period, type of hormonal therapy received, family history and number of children. To ensure patient confidentiality, all identifiable data was removed, and the dataset was structured using automated segmentation and manual verification to ensure quality and transparency. This dataset is an invaluable resource for both medical and AI research communities. It provides real-world data for developing and testing NLP algorithms and machine learning models, specifically for automating BI-RADS classification and analyzing mammography reports.
PB Elsevier
YR 2025
FD 2025-06-07
LK http://hdl.handle.net/20.500.14066/4619
UL http://hdl.handle.net/20.500.14066/4619
LA eng
NO Vázquez Noguera, J. L., Torres-Hurtado, A., Gómez-Adorno, H., Mello-Román, J. C., Fleitas-Alvarez, E. J., Espinola Schulze, F. F., Garcia-Torres, M., Méndez Gaona, C. D., Gardel Sotomayor, P. E., Vázquez Noguera, S., Zaracho Amarilla, N. E., & Gamarra Esquivel, O. W. (2025). Mammography reporting dataset with BI-RADS system for natural language processing applications: addressing public data gaps in Spanish. Data in Brief, 61, Article 111761. https://doi.org/10.1016/j.dib.2025.111761
NO Corresponding author. E-mail address: helena.gomez@iimas.unam.mx (H. Gómez-Adorno). Social media: X @helen_py (H. Gómez-Adorno).
NO Data accessibility.Repository name: Zenodo.Data identification number: 10.5281/zenodo.14827680.Direct URL to data: https://zenodo.org/records/14827680.
NO Consejo Nacional de Ciencia y Tecnología
DS MINDS@UW
RD 03-sep-2026