Source:

Miguel Patrício(miguelpatricio '@' gmail.com), José Pereira (jafcpereira '@' gmail.com), Joana Crisóstomo (joanacrisostomo '@' hotmail.com), Paulo Matafome (paulomatafome '@' gmail.com), Raquel Seiça (rmfseica '@' gmail.com), Francisco Caramelo (fcaramelo '@' fmed.uc.pt), all from the Faculty of Medicine of the University of Coimbra and also Manuel Gomes (manuelmgomes '@' gmail.com) from the University Hospital Centre of Coimbra

Data Set Information:

There are 10 predictors, all quantitative, and a binary dependent variable, indicating the presence or absence of breast cancer.
The predictors are anthropometric data and parameters which can be gathered in routine blood analysis.
Prediction models based on these predictors, if accurate, can potentially be used as a biomarker of breast cancer.

Attribute Information:

Quantitative Attributes:
Age (years)
BMI (kg/m2)
Glucose (mg/dL)
Insulin (µU/mL)
HOMA
Leptin (ng/mL)
Adiponectin (µg/mL)
Resistin (ng/mL)
MCP-1(pg/dL)

Labels:
1=Healthy controls
2=Patients

Relevant Papers:

[Web Link]
[Web Link]

Citation Request:

This dataset is publicly available for research. The details are described in [Patricio, 2018] - [Web Link].
Please include this citation if you plan to use this database:
[Patricio, 2018] Patrício, M., Pereira, J., Crisóstomo, J., Matafome, P., Gomes, M., Seiça, R., & Caramelo, F. (2018). Using Resistin, glucose, age and BMI to predict the presence of breast cancer. BMC Cancer, 18(1). [Web Link]

Supported By:

 In Collaboration With: