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Improved detection of human breast lesions following experimental training
Author(s) -
Hall Deborah C.,
Adams Calvin K.,
Stein Gerald H.,
Stephenson Hester S.,
Goldstein Mark K.,
Pennypacker H. S.
Publication year - 1980
Publication title -
cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.052
H-Index - 304
eISSN - 1097-0142
pISSN - 0008-543X
DOI - 10.1002/1097-0142(19800715)46:2<408::aid-cncr2820460233>3.0.co;2-p
Subject(s) - medicine , false positive paradox , confidence interval , breast examination , true positive rate , radiology , breast cancer , mammography , artificial intelligence , cancer , computer science
This study was designed to evaluate the effect of breast examination training with silicone models on the detection of lesions in natural breast tissue. Six women with a total of 13 benign breast lumps were examined by 20 trainees before and after a 20–30 minute training session or a period of unrelated activity. Following the training, percentage of correct detections, duration of examination, and reports of false positives increased. Confidence in correct detections and false positives also increased, although confidence in correct detections was greater than confidence in false positives. The results indicate the effectiveness of the training and suggest a need for a more complex model for training discrimination between normal nodularity and breast lesions.