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Coimbra Health Study: Breast Cancer Data
Patient Health Records & Digital Health
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About
Clinical features from the Coimbra Breast Cancer Study offer a detailed look into the physiological and metabolic profiles of 64 breast cancer patients and 52 healthy individuals. This collection of data provides a valuable resource for analysing the complex relationships between various clinical attributes and the presence of breast cancer. It enables the exploration of patterns and correlations that can contribute to a deeper understanding of the factors influencing this health condition.
Columns
- Age: The age of the individual in years.
- BMI: Body Mass Index, a measure of body fat calculated from weight and height (kg/m²).
- Glucose: The level of glucose in the blood (mg/dL).
- Insulin: The level of insulin, a hormone that regulates glucose (µU/mL).
- HOMA: Homeostatic Model Assessment, an index used to quantify insulin resistance and beta-cell function.
- Leptin: The level of leptin, a hormone involved in regulating appetite and energy balance (ng/mL).
- Adiponectin: The level of adiponectin, a protein connected to metabolic regulation (µg/mL).
- Resistin: The level of resistin, a protein implicated in insulin resistance (ng/mL).
- MCP-1: Monocyte Chemoattractant Protein-1, a cytokine involved in inflammatory responses (pg/dL).
- Classification: A binary label indicating the individual's status (1 for Healthy controls, 2 for Patients with breast cancer).
Distribution
The data is structured in a CSV file format, containing 116 records across 10 distinct columns. There are no missing or mismatched values within the file.
Usage
This dataset is well-suited for developing and testing predictive models for breast cancer detection. It can be used for exploratory data analysis to identify potential biomarkers and understand the interplay between metabolic indicators and breast cancer. It is also a versatile resource for supervised machine learning tasks, specifically binary classification.
Coverage
The dataset includes clinical data for 116 individuals, composed of 64 breast cancer patients and 52 healthy controls. The age of participants ranges from 24 to 89 years.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
- Healthcare Professionals and Medical Researchers: To analyse factors influencing breast cancer and identify potential biomarkers.
- Data Scientists and Machine Learning Engineers: For building and validating predictive models for binary classification tasks.
- Students and Academics: As a practical dataset for projects and research in the fields of oncology, endocrinology, and data analysis.
Dataset Name Suggestions
- Coimbra Breast Cancer Clinical Features
- Metabolic Indicators in Breast Cancer Patients
- Breast Cancer Predictive Biomarkers Study
- Clinical Profile of Breast Cancer vs Healthy Controls
- Coimbra Health Study: Breast Cancer Data
Attributes
Original Data Source: Coimbra Health Study: Breast Cancer Data
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