Skip to content

A quick and simple analysis on the classic dataset found in the UCI Repository

Notifications You must be signed in to change notification settings

MariosKokmo/Mammographic_masses

Repository files navigation

Mammographic_masses

A quick and simple analysis on the classic dataset found in the UCI Repository,

Mammography is the most effective method for breast cancer screening available today. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approximately 70% unnecessary biopsies with benign outcomes. To reduce the high number of unnecessary breast biopsies, several computer-aided diagnosis (CAD) systems have been proposed in the last years.These systems help physicians in their decision to perform a breast biopsy on a suspicious lesion seen in a mammogram or to perform a short term follow-up examination instead. This data set can be used to predict the severity (benign or malignant) of a mammographic mass lesion from BI-RADS attributes and the patient's age. It contains a BI-RADS assessment, the patient's age and three BI-RADS attributes together with the ground truth (the severity field) for 516 benign and 445 malignant masses that have been identified on full field digital mammograms collected at the Institute of Radiology of the University Erlangen-Nuremberg between 2003 and 2006. Each instance has an associated BI-RADS assessment ranging from 1 (definitely benign) to 5 (highly suggestive of malignancy) assigned in a double-review process by physicians. Assuming that all cases with BI-RADS assessments greater or equal a given value (varying from 1 to 5), are malignant and the other cases benign, sensitivities and associated specificities can be calculated. These can be an indication of how well a CAD system performs compared to the radiologists.

Class Distribution: benign: 516; malignant: 445

6 Attributes in total (1 goal field, 1 non-predictive, 4 predictive attributes)

  1. BI-RADS assessment: 1 to 5 (ordinal, non-predictive!)
  2. Age: patient's age in years (integer)
  3. Shape: mass shape: round=1 oval=2 lobular=3 irregular=4 (nominal)
  4. Margin: mass margin: circumscribed=1 microlobulated=2 obscured=3 ill-defined=4 spiculated=5 (nominal)
  5. Density: mass density high=1 iso=2 low=3 fat-containing=4 (ordinal)
  6. Severity: benign=0 or malignant=1 (binominal, goal field!)

Missing Attribute Values:

  • BI-RADS assessment: 2
  • Age: 5
  • Shape: 31
  • Margin: 48
  • Density: 76
  • Severity: 0

About

A quick and simple analysis on the classic dataset found in the UCI Repository

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published