A step toward computer-assisted mammography using evolutionary programming and neural networks.
Artificial intelligence techniques can be used to provide a second opinion in medical settings. This may improve the sensitivity and specificity of diagnoses, as well as the cost effectiveness of the physician's effort. In the current study, evolutionary programming is used to train artificial neural networks to detect breast cancer using radiographic features and patient age. Results from 112 suspicious breast masses (63 malignant, 49 benign, biopsy proven) indicate that a significant probability of detecting malignancies can be achieved using simple neural architectures at the risk of a small percentage of false positives.
Fogel
D B
DB
Natural Selection, Inc., 3333 N. Torrey Pines Ct., Suite 200, La Jolla, CA 92037, USA. dfogel@natural-selection.com
Wasson
E C
EC
Boughton
E M
EM
Porto
V W
VW
D000465:Algorithms; D005075:Biological Evolution; D001943:Breast Neoplasms / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D016571:Neural Networks, Computer; D012372:ROC Curve