Commit Inicial

data/tanveer/mammographic/mammographic_masses.names

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+1. Title: Mammographic Mass Data
+
+2. Sources:
+
+   (a) Original owners of database:
+        Prof. Dr. R<>diger Schulz-Wendtland
+        Institute of Radiology, Gynaecological Radiology, University Erlangen-Nuremberg
+        Universit<69>tsstra<72>e 21-23
+        91054 Erlangen, Germany
+        
+   (b) Donor of database:
+        Matthias Elter
+        Fraunhofer Institute for Integrated Circuits (IIS)
+        Image Processing and Medical Engineering Department (BMT) 
+        Am Wolfsmantel 33
+        91058 Erlangen, Germany
+        matthias.elter@iis.fraunhofer.de
+        (49) 9131-7767327 
+        
+   (c) Date received: October 2007
+ 
+3. Past Usage:
+    M. Elter, R. Schulz-Wendtland and T. Wittenberg (2007)
+    The prediction of breast cancer biopsy outcomes using two CAD approaches that both emphasize an intelligible decision process.
+    Medical Physics 34(11), pp. 4164-4172
+
+4. Relevant Information:
+    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.
+
+5. Number of Instances: 961
+
+6. Number of Attributes: 6 (1 goal field, 1 non-predictive, 4 predictive attributes)
+
+7. Attribute Information:
+   1. BI-RADS assessment: 1 to 5 (ordinal)  
+   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)
+
+8. Missing Attribute Values: Yes
+    - BI-RADS assessment:    2
+    - Age:                   5
+    - Shape:                31
+    - Margin:               48
+    - Density:              76
+    - Severity:              0
+
+9. Class Distribution: benign: 516; malignant: 445