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Computer-assisted cytologic diagnosis in pancreatic FNA: An application of neural networks to image analysis.

Amir Momeni BoroujeniElham YousefiJonathan Somma
Published in: Cancer cytopathology (2017)
The results of the current study demonstrate that computer models can be used successfully to distinguish benign from malignant pancreatic cytology. The fact that the model can categorize atypical cases into benign or malignant with 77% accuracy highlights the great potential of this technology. Although further study is warranted to validate its clinical applications in pancreatic and perhaps other areas of cytology as well, the potential for improved patient outcomes using MNN for image analysis in pathology is significant. Cancer Cytopathol 2017;125:926-33. © 2017 American Cancer Society.
Keyphrases
  • fine needle aspiration
  • papillary thyroid
  • neural network
  • high grade
  • squamous cell
  • ultrasound guided
  • squamous cell carcinoma
  • young adults
  • childhood cancer
  • human health
  • lymph node metastasis