Artificial Intelligence in Cytopathology: A Neural Network to Identify Papillary Carcinoma on Thyroid Fine-Needle Aspiration Cytology Smears

Introduction: Fine-needle aspiration cytology (FNAC) for identification of papillary carcinoma thyroid is a moderately sensitive and specific modality. The present machine learning tools can correctly classify images into broad categories. Training software for recognition of papillary thyroid carci...

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Veröffentlicht in:	Journal of pathology informatics Jg. 9; H. 1; S. 43
Hauptverfasser:	Sanyal, Parikshit, Mukherjee, Tanushri, Barui, Sanghita, Das, Avinash, Gangopadhyay, Prabaha
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Inc 01.01.2018 Wolters Kluwer India Pvt. Ltd Medknow Publications & Media Pvt. Ltd Medknow Publications & Media Pvt Ltd Elsevier
Schlagworte:	Arrays Artificial intelligence Artificial neural networks Automation Cellular biology Classification Cytology Datasets Diagnostic systems fine-needle aspiration cytology Image classification Learning theory Lesions Machine learning Medical imaging Microphotographs neural network Neural networks Object recognition Original Programming languages Software thyroid Thyroid cancer Thyroid gland Training cytology fine-needle aspiration cytology image classification thyroid Artificial intelligence neural network
ISSN:	2153-3539, 2229-5089, 2153-3539
Online-Zugang:	Volltext
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