title: Artificial neural network analysis for evaluating cancer risk in multinodular goiter.
abstract: BACKGROUND
  The aim of this study was to create a diagnostic model using the artificial neural networks (ANNs) to predict malignancy in multinodular goiter patients with an indeterminate cytology.
  
  
  METHODS
  Out of 623 patients, 411 evaluated for multinodular goiter between July 2004 and March 2010 had a fine-needle aspiration biopsy. All patients underwent total thyroidectomy. The interpretation was consistent with an indeterminate lesion in 116 (18.6%) patients. Patient's medical records including age, sex, dominant nodule size, pre-operative serum thyroid-stimulating hormone level, thyroid hormone therapy and final pathologic diagnosis were collected retrospectively.
  
  
  RESULTS
  The mean age of the patients was 44.6 years (range, 17-78 years). About 104 (89.7%) were female and 12 (10.3%) were male patients. Final pathology revealed 24 malignant diseases (20.7%) and 92 (79.3%) benign diseases. After the completion of training, the ANN model was able to predict diagnosis of malignancy with a high degree of accuracy. The area under the curve of ANNs was 0.824.
  
  
  CONCLUSIONS
  The ANNs technique is a useful aid in diagnosing malignancy and may help reduce unnecessary thyroidectomies in multinodular goiter patients with an indeterminate cytology. Further studies are needed to construct the optimal diagnostic model and to apply it in the clinical practice.
authors: Department of Surgery, Ankara Numune Training and Research Hospital, Ankara, Turkey.
authors: Baris
authors: B
authors: Saylam
authors: Department of Surgery, Ankara Numune Training and Research Hospital, Ankara, Turkey.
authors: Mehmet
authors: M
authors: Keskek
authors: Department of Surgery, Ankara Numune Training and Research Hospital, Ankara, Turkey.
authors: Sönmez
authors: S
authors: Ocak
authors: Department of Surgery, Ankara Numune Training and Research Hospital, Ankara, Turkey.
authors: Ali Osman
authors: AO
authors: Akten
authors: Department of Surgery, Ankara Numune Training and Research Hospital, Ankara, Turkey.
authors: Mesut
authors: M
authors: Tez
keywords: Artificial neural network; fine-needle aspiration; multinodular goiter; thyroid; ındeterminate cytology